Merge pull request #1048 from ruvnet/fix/issues-1031-894-fusion-guard-model-load

fix: multistatic fusion guard for real TDM (#1031) + load published HF model via auto-detect/convert (#894)
test(engine): update contradiction_demotes_privacy for #1031 guard thresholds
2026-06-14 11:03:18 +00:00 · 2026-06-13 12:23:06 -04:00 · 2026-06-13 12:14:11 -04:00 · 2026-06-13 12:05:05 -04:00 · 2026-06-13 12:04:47 -04:00 · 2026-06-13 00:46:29 -04:00
34 changed files with 3818 additions and 38 deletions
@@ -7,6 +7,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ## [Unreleased]

+### Fixed
+- **Multistatic fusion guard was too tight for real TDM hardware (#1031).** `MultistaticConfig::default().guard_interval_us` was 5,000 µs (5 ms) with a comment claiming "well within the 50 ms TDMA cycle" — but on a real N-slot TDM schedule node `k` transmits in slot `k`, so two nodes are separated by the *slot offset*, not clock jitter. A real 2-node mesh (slots 0/1) measured an **18,194 µs** spread, so every real frame set exceeded the 5 ms guard and `fuse()` silently fell back to per-node sum/dedup — multistatic fusion never actually ran on hardware. Raised the default hard guard to **60 ms** (a full 50 ms TDMA cycle + 20% jitter headroom, derived from the slot model and documented in the field doc) and the soft guard to **20 ms** (just above the observed 18.2 ms 2-slot spread, so a normal cycle fuses cleanly with no privacy demotion). Added `MultistaticConfig::for_tdm_schedule(total_slots, slot_duration_us)` to derive the guard from a deployment's exact schedule, and a `WDP_TDM_SLOTS`+`WDP_TDM_SLOT_US` env seam in sensing-server. The honest per-node fallback remains for genuinely-mismatched frames — now the exception, not the default. Pinned by `fuse_real_tdm_spread_18194us_fuses_with_default_guard` (fails on the old 5 ms default) + `configurable_guard_rejects_too_large_spread` (guard still rejects a spread beyond one cycle).
+- **Published HuggingFace model was unloadable — RVF format mismatch (#894).** The `ProgressiveLoader` rejected the published `ruvnet/wifi-densepose-pretrained` model with the opaque `invalid magic at offset 0: expected 0x52564653 (RVFS), got 0x77455735`, then silently fell back to signal heuristics (the "10 persons for 1" garbage reporters saw). The HF repo ships `model.safetensors`, `model-q{2,4,8}.bin` (magic `0x77455735` = "5WEw"), and `model.rvf.jsonl` — none carry the binary-RVF magic. New `model_format` module **auto-detects** RVFS / safetensors / HF-quant-bin / JSONL by magic+name, returns a **typed actionable** `ModelLoadError` (lists accepted formats + the one-command convert path — never the opaque magic), and **converts** `model.safetensors` / `model.rvf.jsonl` → RVF in-memory so the published full-precision model now loads via `--model`. A `--convert-model <in> --convert-out <out>` CLI subcommand gives a one-command offline path; the silent heuristics fallback is now a loud, actionable error. **Honest scope:** the converter wires the format/load path (safetensors F32 tensors → RVF weight segment, manifest written, Layer A/B/C all succeed, weights round-trip) — it does **not** claim end-to-end pose accuracy, since the HF pose-decoder architecture differs from this crate's inference head (still data-gated in #894). Quantized `.bin` blobs are rejected with a typed error pointing at the safetensors path. Pinned by `safetensors_converts_and_loads` + `hf_quant_classifies_to_actionable_error` (both fail on the old opaque-magic path).
+
 ### Changed
 - **Mesh partition risk now demotes the privacy class and is witnessed (ADR-032).** The dynamic min-cut guard's `at_risk` signal was advisory-only (it fed the recalibration advisor). It now also contributes to the ADR-141 privacy demotion alongside fusion- and array-level contradictions: a mesh close to partitioning makes the fused belief less trustworthy, so the cycle emits at a more restricted class (monotonic — information only removed). Because `effective_class` feeds the BLAKE3 witness, a fragmenting array now shifts the witness — partition risk is auditable, not just logged. The mesh computation moved ahead of the demotion step in `process_cycle`; new `mesh_guard_mut()` exposes risk-threshold tuning. Test proves a forced-risk 3-node cycle demotes PrivateHome Anonymous→Restricted and shifts the witness vs a clean *same-topology* baseline (the only delta between the two cycles is the forced risk).

@@ -0,0 +1,132 @@
+# Edge-Skill Synthetic-Ground-Truth Validation — RESULTS
+
+**Crate:** `v2/crates/wifi-densepose-wasm-edge` (workspace-EXCLUDED — build from its own dir)
+**Branch:** `feat/edge-skills-synthetic-validation`
+**ADR:** [ADR-160](../../docs/adr/ADR-160-edge-skill-library-honest-labeling.md)
+**Date:** 2026-06-13
+**Harness:** `tests/synthetic_validation.rs`
+
+> **HONESTY BOUNDARY — read first.** Everything below is **synthetic-ground-truth
+> validation**: a signal is *planted* with a known answer, the **real** detector
+> is run, and detection accuracy / precision / recall / rate-error is **measured**.
+> This is **NOT field accuracy.** A skill that recovers a planted sinusoid here is
+> proven to do the math it claims on a *constructed* signal; it is **NOT** proven
+> to work on real CSI in a real room. Skills whose detection target cannot be
+> honestly planted (clinical, weapon, affect, sleep-stage, sign-language) are
+> **NOT** given a number — they are listed under **DATA-GATED** with the real
+> data each would require.
+
+## Reproduce
+
+```bash
+cd v2/crates/wifi-densepose-wasm-edge   # workspace-excluded; build here
+cargo test --features std --test synthetic_validation -- --nocapture
+# also runs under the medical tier (med_* skills stay DATA-GATED, not validated):
+cargo test --features std,medical-experimental --test synthetic_validation -- --nocapture
+```
+
+Each `MEASURED-on-synthetic | …` line printed by the harness is the source of the
+table below. Numbers are deterministic (no RNG; pseudo-noise uses a fixed LCG seed).
+
+---
+
+## MEASURED-on-synthetic (constructible skills)
+
+| Skill | What was planted (ground truth) | Result | Grade |
+|-------|----------------------------------|--------|-------|
+| **vital_trend** | BPM held N≥6 calls at each threshold band (brady/tachy-pnea <12 / >25, brady/tachy-cardia <50 / >120, apnea breathing<1.0 for ≥20) vs normal | **acc 1.000, prec 1.000, recall 1.000** (TP5 FP0 TN5 FN0) | MEASURED |
+| **exo_time_crystal** | period-2 coordinated motion vs pseudo-noise + flat | **acc 1.000** (TP1 FP0 TN2 FN0) | MEASURED † |
+| **exo_ghost_hunter** (hidden breathing) | phase sinusoid at lag-8 (breathing band 5–15) in an empty room vs flat phase | **acc 1.000**; planted score **1.000**, flat **0.000** | MEASURED |
+| **occupancy** | 220-frame flat-amplitude calibration, then strong per-zone amplitude variance vs flat | **acc 1.000** (TP1 FP0 TN1 FN0) | MEASURED |
+| **intrusion** | calibrate→arm (330 quiet frames), then per-subcarrier Δphase>1.5 + Δamp≫3σ vs quiet | **acc 1.000** (TP1 FP0 TN1 FN0) | MEASURED |
+| **exo_rain_detect** | empty room, 60-frame baseline, then broadband variance (8/8 groups, ratio≫2.5) for ≥10 frames vs stable-low | **acc 1.000** (TP1 FP0 TN1 FN0) | MEASURED |
+| **sig_flash_attention** | sustained high phase+amplitude in each of the 8 subcarrier groups; assert reported attention peak == planted group | **peak-localization 8/8 = 1.000** | MEASURED |
+| **spt_spiking_tracker** | sparse (2-subcarrier) large phase-delta in each of the 4 zones; assert tracked zone == planted zone | **zone-localization 4/4 = 1.000** | MEASURED ‡ |
+| **sig_optimal_transport** | sustained large frame-to-frame amplitude-distribution change vs stationary | **acc 1.000** (TP1 FP0 TN1 FN0) | MEASURED |
+| **sig_mincut_person_match** | 2 persons with distinct stable per-region variance signatures over 40 frames | **person ids assigned, 0 id-swaps / 40 frames** | MEASURED |
+| **lrn_dtw_gesture_learn** | stillness → 3 identical gesture rehearsals → enrollment | **template enrolled (templates=1)** | MEASURED (enroll) §|
+| **sig_sparse_recovery** | 30 clean frames to init, then 8/32 (25%) nulled subcarriers | **dropout-detect + recovery-trigger = PASS** | MEASURED (trigger) ¶|
+
+### Caveats on individual results
+
+† **exo_time_crystal — honest discriminative limit.** A *pure* periodic signal
+already has autocorrelation peaks at lag L **and** 2L (natural harmonics), so this
+"period-doubling" detector cannot separate a true period-2 sub-harmonic from a
+plain periodic signal — an earlier plant using a clean sine produced a *false
+positive* (recorded during development). The construct it **can** discriminate
+with known ground truth is **periodic-coordination vs aperiodic** (noise/flat),
+which is what is measured (1.000). The original "sub-harmonic vs clean period"
+claim is **NOT** validatable with this algorithm.
+
+‡ **spt_spiking_tracker — plant must be sparse.** With weights init'd home=1.0 /
+cross=0.25, firing all 8 inputs in a zone (8×0.25=2.0 > threshold 1.0) overdrives
+*every* output neuron and the tracker collapses to zone 0 (measured 1/4 during
+development). Firing only 2 inputs (home 2.0 fires, cross 0.5 silent) yields clean
+4/4 zone localization. The validatable claim is *single-zone* localization.
+
+§ **lrn_dtw_gesture_learn — enrollment validated; replay-match NOT.** The
+deterministic, constructible part (stillness → 3 identical rehearsals → a template
+is enrolled) is MEASURED. The DTW *replay match* (731) did **not** fire on the
+identical replay in this run (`match_same=false`) — replay-recognition accuracy is
+**reported, not asserted**, and is not claimed as validated.
+
+¶ **sig_sparse_recovery — trigger validated; recovery accuracy is NEGATIVE.**
+The dropout-detection + ISTA-recovery *trigger* pipeline fires correctly on >10%
+planted nulls (asserted). But the **measured recovery accuracy is NOT a win**:
+recovered RMSE **1.0045** vs unrecovered-null RMSE **0.9830** (**−2.2%**, i.e.
+slightly *worse* than leaving the nulls at zero) on a neighbor-correlated signal.
+The tridiagonal correlation model's fixed point does not equal the planted truth.
+**The recovery's reconstruction quality is therefore NOT validated as effective on
+synthetic data** — only its detection/trigger path is. Reported honestly; no
+positive number claimed.
+
+---
+
+## DATA-GATED — NOT validatable on synthetic data
+
+Planting a "seizure-like" / "weapon-like" / "happy-like" synthetic signal and
+claiming the detector "works" validates **nothing real** and is exactly the
+AI-slop this project fights. These skills run real DSP (per ADR-160, 0 stubs) and
+keep their ADR-160 disclaimers, but get **no accuracy number** here. Each needs
+the specific real, labelled data listed:
+
+| Skill | Why not constructible on synthetic | Real data required |
+|-------|------------------------------------|--------------------|
+| `med_seizure_detect` | "seizure-like" motion is not a seizure; no ground-truth signature exists synthetically | Clinical EEG-/video-labelled tonic-clonic seizure CSI from instrumented patients |
+| `med_sleep_apnea` | a planted breathing-pause is not clinical apnea (AHI scoring, hypopnea, desaturation) | Polysomnography-labelled (PSG) overnight CSI with scored apnea/hypopnea events |
+| `med_cardiac_arrhythmia` | a synthetic HR sequence cannot encode true arrhythmia morphology | ECG-labelled CSI (AFib/PVC/etc.) from clinical monitoring |
+| `med_respiratory_distress` | distress is a clinical gestalt, not a plantable rate | Clinician-labelled respiratory-distress CSI episodes |
+| `med_gait_analysis` | clinical gait metrics need a reference motion-capture standard | Mocap-/force-plate-labelled gait CSI |
+| `sec_weapon_detect` | a high variance ratio is RF reflectivity, **not** weapon discrimination (ADR-160 §A3 already renamed the event to `HIGH_METAL_REFLECTIVITY`) | Labelled metal-object-vs-no-object CSI with controlled object classes |
+| `exo_emotion_detect` | affect is not recoverable from a planted heuristic; outputs are proxies (ADR-160 §A2) | Validated affect-labelled CSI (self-report / physiological ground truth) |
+| `exo_happiness_score` | "happiness" is a gait-energy proxy, not a measured affect (ADR-160 §A2) | Validated affect/valence-labelled CSI |
+| `exo_dream_stage` | sleep staging needs PSG reference (EEG/EOG/EMG) | PSG-staged overnight CSI |
+| `exo_gesture_language` | coarse gesture clusters ≠ true sign language (ADR-160 §A4) | Labelled ASL letter/word CSI dataset |
+
+> The above are **not failures** — they are the honest boundary. A smaller set of
+> genuinely-measured skills plus this explicit gated list is the deliverable, per
+> the prove-everything directive.
+
+---
+
+## Skills not in either list
+
+The remaining edge skills (smart-building / retail / industrial occupancy-style,
+the other `sig_*`/`lrn_*`/`spt_*`/`tmp_*`/`qnt_*`/`aut_*`/`ais_*` algorithm-named
+modules) are **wired and exercised live** in the unified pipeline integration test
+(`tests/pipeline_all.rs`, all 59 default / 64 medical skills run without panic over
+300 synthetic frames) but were **not** given an individual planted-ground-truth
+accuracy number here. They are honest REAL-DSP modules (ADR-160) whose physical
+observable could be planted with more harness work; that is deferred, not claimed.
+
+## Test counts (full crate suite)
+
+```
+DEFAULT  (--features std):                     631 passed, 0 failed
+  (lib 504; budget 25; honest_labeling 10; pipeline_all 4; synthetic_validation 12; bench 1; vendor 75)
+MEDICAL  (--features std,medical-experimental): 669 passed, 0 failed
+  (lib 542; +16 same new tests; med_* stay DATA-GATED, not validated)
+```
+
+(M6 baseline was 615 / 653; the new pipeline_all (4) + synthetic_validation (12)
+tests add 16 to each tier.)
@@ -0,0 +1,130 @@
+# ADR-132: HOMECORE-RECORDER — State History + Semantic Search
+
+| Field | Value |
+|-------|-------|
+| **Status** | Accepted |
+| **Date** | 2026-05-25 |
+| **Deciders** | ruv |
+| **Codename** | **HOMECORE-RECORDER** |
+| **Crate** | `v2/crates/homecore-recorder` |
+| **Relates to** | [ADR-126](ADR-126-ruview-native-ha-port-master.md) (HOMECORE master — series map row ADR-132), [ADR-127](ADR-127-homecore-state-machine-rust.md) (HOMECORE-CORE state machine), [ADR-124](ADR-124-rvagent-mcp-ruvector-npm-integration.md) (ruvector/SENSE-BRIDGE), [ADR-130](ADR-130-homecore-rest-websocket-api.md) (HOMECORE-API query surface, downstream) |
+| **Tracking issue** | [#800](https://github.com/ruvnet/RuView/pull/800) (HOMECORE intake) |
+
+> **Documented retroactively (2026-06-12).** The `homecore-recorder` crate shipped under
+> the ADR-126 series map (which planned an "ADR-132 HOMECORE-RECORDER") but the standalone
+> ADR file was never written; the crate's `Cargo.toml`, `README.md`, `lib.rs`, `schema.rs`,
+> and `semantic.rs` all cite "ADR-132". This ADR reverse-documents the decision that the
+> shipped, tested code already embodies (ADR-164 Gap G3 / Coverage-Gaps Lens §A). It does
+> **not** introduce new design; it records what is built. Date reflects the crate's intake
+> era (first commit `e96ebaea8`, 2026-05-25); real-impl pass landed in `7c8071145`
+> (2026-06-11).
+
+---
+
+## 1. Context
+
+ADR-126 (the HOMECORE master) decided to reimplement Home Assistant (HA) natively in Rust.
+HA persists every state change to a SQLite *recorder* database; downstream features
+(history graphs, the logbook, long-term statistics, automation conditions that reference
+past state) all read that store. HOMECORE therefore needs a durable state-history backbone.
+
+Two forces shape the decision:
+
+1. **Migration / coexistence.** Users adopting HOMECORE will have an existing HA
+   `recorder` database. Reusing HA's on-disk schema (rather than inventing a new one) lets
+   HOMECORE read an existing HA `home-assistant_v2.db` directly and lets HA-aware tooling
+   read HOMECORE's store. This is the same trust boundary that `homecore-migrate`
+   (ADR-165) handles for `.storage/*.json`.
+2. **Semantic queries.** HA history is queried with SQL `BETWEEN`/`WHERE` clauses. The
+   HOMECORE platform already carries ruvector (ADR-124) for vector search, so the recorder
+   can additionally embed state changes and answer natural-language queries
+   ("which kitchen devices were warm at 3 PM?") via k-NN — a capability HA does not have.
+
+The recorder is the **durable-state surface**: if it is wrong, history, logbook, and
+historical-condition automations are all wrong. ADR-164 flagged it as a CRITICAL coverage
+gap precisely because such a load-bearing crate had no governing ADR.
+
+## 2. Decision
+
+Ship `homecore-recorder` as a SQLite state-history recorder with an HA-compatible schema
+and an optional ruvector-backed semantic index, in three phases. P1 and P2 are built and
+tested; P3 is planned.
+
+### 2.1 Storage — SQLite with the HA recorder schema (P1, shipped)
+
+- Persist via `sqlx` with the SQLite backend only (no Postgres, no TLS feature set).
+- Mirror HA recorder **schema v48** so the store is bidirectionally readable
+  (`src/schema.rs`):
+  - `state_attributes` — shared attribute JSON blobs, deduped by an FNV-1a 64-bit hash
+    stored as a signed `i64` (matches HA's dedup key);
+  - `states` — one row per state write (`entity_id`, `state`, `attributes_id` FK,
+    `last_changed_ts`/`last_updated_ts` as REAL Unix seconds, `context_id` UUID);
+  - `events` — domain events (`event_type`, `event_data` JSON, `time_fired_ts`);
+  - `recorder_runs` — boot/shutdown bookends for history-gap detection.
+- All DDL uses `CREATE TABLE IF NOT EXISTS`, so schema application is idempotent and safe
+  on every startup.
+- Default persistence path `.homecore/home.db` (configurable).
+
+### 2.2 Capture — listener on the HOMECORE event bus (P1, shipped)
+
+- `RecorderListener` subscribes to the HOMECORE event bus (ADR-127) and captures
+  `StateChanged` events, writing snapshots through `Recorder` (`src/listener.rs`,
+  `src/db.rs`).
+- A `DedupEngine` (`src/dedup.rs`) skips redundant writes when the state hash is unchanged,
+  matching HA's stateful-listener behaviour.
+
+### 2.3 Semantic search — ruvector HNSW (P2, shipped, feature-gated)
+
+- Behind the `ruvector` Cargo feature, the `Recorder` additionally calls a `SemanticIndex`
+  implementation (`src/semantic.rs`) that embeds state attributes and stores vectors in a
+  `ruvector-core` HNSW index for k-NN search.
+- P2 embeddings are **hash-based** (sha2) — a deliberate, honest placeholder. They give a
+  working HNSW surface without claiming sentence-level semantic quality.
+- When the feature is off, `NullSemanticIndex` satisfies the `SemanticIndex` trait bound
+  with no allocation, so the structural recorder ships independently of ruvector.
+
+### 2.4 Real sentence embeddings (P3, planned — not yet built)
+
+- Replace the hash embeddings with ruvector-attention sentence embeddings (dim → 384). Not
+  implemented; tracked as a follow-up. The README and `Cargo.toml` label this P3 explicitly.
+
+### 2.5 Test evidence (as shipped)
+
+- P1: 14 tests (`cargo test -p homecore-recorder --no-default-features`).
+- P2: 20 tests (`cargo test -p homecore-recorder --features ruvector`).
+
+## 3. Consequences
+
+**Positive.**
+
+- HA-schema compatibility makes migration (ADR-165) and coexistence cheap: HOMECORE can
+  read an existing HA `recorder.db`, and any SQLite tool can read HOMECORE's history.
+- The semantic index is **additive** and feature-gated: the durable structural recorder has
+  no hard dependency on ruvector, so the storage backbone ships first.
+- Standard SQLite means no proprietary export format; history is directly queryable.
+
+**Negative / honest limits.**
+
+- P2 semantic search uses **hash embeddings**, not real sentence embeddings — query quality
+  is limited until P3. This is disclosed in the crate docs and here; it must not be cited as
+  semantic-quality-validated.
+- No per-crate benchmarks exist yet; the latency figures in the README
+  (state-write p50 < 2 ms, semantic search < 10 ms on 1 M records) are design targets /
+  estimates, **needs verification** with a criterion baseline.
+- Pinning to HA schema v48 couples HOMECORE to a specific HA recorder schema generation;
+  future HA schema bumps require an explicit migration step.
+
+**Neutral.**
+
+- This ADR governs the recorder crate only. The query/REST surface over recorder data is
+  HOMECORE-API (ADR-130, P3); automation conditions on historical state are
+  HOMECORE-automation (ADR-129, P3).
+
+## 4. Links
+
+- Crate: `v2/crates/homecore-recorder/` — `Cargo.toml`, `README.md`, `src/lib.rs`,
+  `src/db.rs`, `src/schema.rs`, `src/dedup.rs`, `src/listener.rs`, `src/semantic.rs`.
+- [ADR-126](ADR-126-ruview-native-ha-port-master.md) — HOMECORE master (series map: ADR-132 = HOMECORE-RECORDER).
+- [ADR-165](ADR-165-homecore-migrate-from-home-assistant.md) — HOMECORE-MIGRATE (reads HA `.storage`; P2 exports a side-by-side recorder DB).
+- [ADR-164](ADR-164-adr-corpus-gap-analysis.md) — gap analysis that surfaced this missing ADR (Gap G3).
+- [Home Assistant Recorder integration](https://www.home-assistant.io/integrations/recorder/).
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; integration glue pending — see §8 Implementation Status, commit `11f89727f`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-core` (`types.rs`: `CsiFrame`/`CsiMetadata`); `wifi-densepose-signal/src/ruvsense/mod.rs` (`RuvSensePipeline`, six-stage flow); `v2/Cargo.toml` (workspace topology) |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; integration glue pending — see Implementation Status, commit `4fa3847ac`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-signal` (`ruvsense/multistatic.rs` — `fuse`, `attention_weighted_fusion`); `wifi-densepose-ruvector` (`viewpoint/fusion.rs` — `MultistaticArray`); `wifi-densepose-bfld` (`event.rs`) |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; integration glue pending — see Implementation Status, commit `fc7674bde`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-signal` (`ruvsense/multiband.rs`, `ruvsense/multistatic.rs`); `wifi-densepose-ruvector` (`viewpoint/geometry.rs`, `viewpoint/coherence.rs`, `viewpoint/attention.rs`, `viewpoint/fusion.rs`) |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; integration glue pending — see Implementation Status, commit `521a012d8`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | New module/crate `wifi-densepose-worldgraph` alongside `v2/crates/wifi-densepose-geo` and `v2/crates/homecore`; petgraph bridge pattern from `v2/crates/ruv-neural/ruv-neural-graph/src/petgraph_bridge.rs`; integrates `homecore/src/registry.rs` `area_id` and `wifi-densepose-mat/src/domain/scan_zone.rs` |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; integration glue pending — see Implementation Status, commit `169a355bd`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-sensing-server/src/semantic/` (`bus.rs`, `common.rs`); `homecore/src/state.rs` + `event.rs`; `homecore-assist` |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; integration glue pending — see Implementation Status, commit `7d88eb84c`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-bfld` (new module `mode.rs` + `attestation.rs`; extends `lib.rs` `PrivacyClass`, `sink.rs`, `privacy_gate.rs`, `identity_risk.rs`, `emitter.rs`, `ha_discovery.rs`) |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; integration glue pending — see Implementation Status, commit `1f8e180d6`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-signal` (`ruvsense/longitudinal.rs`, `ruvsense/attractor_drift.rs`, `ruvsense/calibration.rs`, `ruvsense/field_model.rs`, `ruvsense/tomography.rs`); `wifi-densepose-bfld` (`privacy_gate.rs`) |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block, v1 fixed-map default; v2 dataset-gated — see Implementation Status, commit `2d4f3dea5`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-signal` (`ruvsense/field_model.rs`, new `ruvsense/rf_slam.rs`); `wifi-densepose-mat` (`tracking/kalman.rs`, `localization/triangulation.rs`); `wifi-densepose-geo`; `wifi-densepose-ruvector` (`mat/triangulation.rs`) |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; no UWB radio in fleet — see Implementation Status, commit `b10bc2e9a`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-hardware` (new UWB driver/parser/auto-detect in `src/`); `wifi-densepose-signal` (`ruvsense/pose_tracker.rs` constraint-aware Kalman update); `wifi-densepose-mat` (`localization/fusion.rs` constraint integration) |
@@ -2,7 +2,7 @@

 | Field | Value |
 |-------|-------|
-| **Status** | Proposed |
+| **Status** | Accepted — partial (built + tested building block; integration glue pending — see Implementation Status, commit `0f336b7d3`) |
 | **Date** | 2026-05-28 |
 | **Deciders** | ruv |
 | **Codebase target** | `wifi-densepose-train` (`src/eval.rs`, `src/metrics.rs`, `src/ruview_metrics.rs`, `src/proof.rs`); `wifi-densepose-signal` (`src/bin/*_proof_runner.rs`); `wifi-densepose-cli` |
@@ -178,10 +178,33 @@ label or behavior change, consistent with leaving their claim surface intact.)

 ## Deferred Backlog (Nothing Dropped)

- **Per-skill accuracy validation** — **DATA-GATED**. Validating any med_*/affect/
-  sign-language claim requires labelled clinical/affective/ASL data and reference
-  standards that do not exist in this repo. The disclaimers + feature gate are the
-  honest stand-in. Nothing is claimed that is not measured.
+- **Per-skill accuracy validation** — **PARTIALLY MEASURED-on-synthetic**
+  (2026-06-13). For the subset of skills whose detection target is *constructible*
+  with known ground truth, a synthetic-ground-truth harness
+  (`tests/synthetic_validation.rs`, 12 tests) plants signals with known answers,
+  runs the real detector, and **measures** detection accuracy / rate-error:
+  `vital_trend`, `exo_time_crystal` (periodic-vs-aperiodic — its sub-harmonic-vs-
+  clean-period claim is NOT separable, recorded honestly), `exo_ghost_hunter`
+  (hidden breathing), `occupancy`, `intrusion`, `exo_rain_detect`,
+  `sig_flash_attention` (8/8 peak localization), `spt_spiking_tracker` (4/4 zone
+  localization, sparse plant), `sig_optimal_transport`, `sig_mincut_person_match`
+  (0 id-swaps), `lrn_dtw_gesture_learn` (enrollment) — all 1.000 where claimed;
+  `sig_sparse_recovery`'s recovery accuracy is reported **negative** (−2.2% vs
+  unrecovered baseline) — only its trigger path is validated. Full numbers +
+  reproduce commands in `benchmarks/edge-skills/RESULTS.md`.
+  The **med_*/affect/sign-language/weapon** claims remain **DATA-GATED**:
+  validating them requires labelled clinical/affective/ASL/metal-object data and
+  reference standards that do not exist in this repo. Planting a "seizure-/weapon-/
+  happy-like" synthetic signal validates nothing real and is explicitly refused;
+  RESULTS.md lists each with the real data it needs. The disclaimers + feature gate
+  are the honest stand-in. Nothing is claimed that is not measured.
+- **Unified edge pipeline** — **MEASURED** (2026-06-13). `src/pipeline_all.rs`
+  (`EdgePipeline`) + `src/skill_registry.rs` register **every** runtime skill
+  behind one uniform `EdgeSkill` trait and run them all per CSI frame; `med_*` are
+  registered only under `--features medical-experimental` (preserves the §A1 gate).
+  `tests/pipeline_all.rs` (4 tests) proves all 59 default / 64 medical skills run
+  without panic over 300 synthetic frames with a well-formed aggregated event
+  stream. `examples/run_all_skills.rs` is a runnable demo. No skill DSP changed.
 - **Criterion benches for `process_frame` budget claims** — **DONE (host)**
  (ADR-163, 2026-06-12). `benches/process_frame_bench.rs` benches the heaviest
  hot paths (`exo_time_crystal` 256×128 autocorrelation, `exo_ghost_hunter`
@@ -0,0 +1,125 @@
+# ADR-164: ADR Corpus Gap Analysis & Remediation Backlog
+
+- **Status:** proposed
+- **Date:** 2026-06-12
+- **Deciders:** ruv
+- **Tags:** governance, meta
+
+## Context
+
+The corpus has grown to **162 ADR entries across 156 distinct files** (ADR-001 through ADR-163, plus 6 duplicate-number collisions). It now spans nine subsystems — signal/DSP, NN/training, ESP32 firmware, RuvSense multistatic, RuView desktop, Cognitum cogs, HOMECORE (HA reimplementation), BFLD privacy, and the streaming engine — written over roughly a year by many agent-driven sessions.
+
+Two forces motivate a corpus-wide gap analysis *now*:
+
+1. **The beyond-SOTA / anti-AI-slop sweep (ADR-154–163) just landed.** That sweep is itself a structured retraction layer: each ADR exists *because* an earlier accepted-or-shipped claim was found false (a dead CIR coherence gate, a fake-gradient TTA path, a self-certifying proof, a WebSocket auth bypass, an inflated survivor count). The sweep hardened five subsystems but was narrowly scoped — it never touched the two largest capability gaps (camera-teacher training validation; federation/BFLD privacy chains). A ledger is needed to record what the sweep retracted and what it left open.
+2. **The status field can no longer be trusted as a source of truth.** A five-lens audit (status-distribution, supersession-chains, contradictions, coverage-gaps, data-hardware-gated) found ~24 ADRs mislabeled `Proposed` while their own commit-pinned Implementation-Status notes report them built and tested; 6 ADR numbers collide; 3 files have no Status header at all. An auditor reading headers would conclude "not built" for landed code, and "built/Accepted" for unvalidated capability.
+
+The detailed lens outputs and the full per-ADR census live in `docs/adr/gap-analysis/` (`lens-findings.md`, `census.md`). This ADR is the authoritative summary and remediation backlog.
+
+## Decision
+
+**This ADR is the authoritative gap ledger and remediation backlog for the ADR corpus as of 2026-06-12.** It does not change any subsystem behavior. It records, with cited ADR ids:
+
+- the status/impl distribution and the bookkeeping-drift problem;
+- a prioritized Gap Register with a recommended action per gap;
+- supersession-integrity defects;
+- the contradiction/retraction list (the anti-slop centerpiece);
+- shipped capabilities with no governing ADR;
+- the genuinely open data/hardware-gated backlog.
+
+Until the Gap Register items are worked, **treat the ADR Status header as advisory, not authoritative**, and treat any accuracy number authored before ADR-155 landed as CLAIMED (not MEASURED) until re-derived through the post-155 leak-free validation split.
+
+## Status Distribution
+
+Counts are approximate (`~`) where a status string is non-canonical or dual-valued; the per-ADR breakdown is in `census.md`.
+
+| Status bucket | Count | impl_state | Count |
+|---|---|---|---|
+| Accepted (incl. partial/in-progress/Phase-1 variants) | ~56 | implemented | ~36 |
+| Proposed (incl. conditional/research-only) | ~88 | partial | ~50 |
+| Superseded | 1 (ADR-002) | proposed-only | ~64 |
+| Rejected | 1 (ADR-098) | stale-or-contradicted | 3 (029/030/031) |
+| Missing / no Status header | 3 (ADR-147-proof, ADR-052-ddd, ADR-134) | unknown | 5 (034/044/052-ddd/147-proof/…) |
+| Mixed/dual status in one ADR | 3 (115, 149×2, 133) | superseded | 1 (ADR-002) |
+
+**Headline:** ~114 of 162 ADRs (≈70%) are decisions that never fully landed (proposed-only + partial + stale + unknown). The dominant failure mode is **stale Status headers**, not abandoned work.
+
+## Gap Register
+
+Severity: CRITICAL (corpus integrity / tooling-breaking / life-safety / security) · HIGH · MEDIUM · LOW. Action vocabulary: *implement · supersede · mark-stale · write-missing-ADR · close-as-gated · renumber · reconcile-docs*.
+
+| ID | Gap | Severity | Affected ADRs | Recommended action |
+|----|-----|----------|---------------|--------------------|
+| G1 | 6 duplicate ADR numbers (two ADRs answer to one number; breaks index/`/adr` tooling) | CRITICAL | 050×2, 052×2, 147×3, 148×2, 149×2, 134 (identity split) | renumber 2-of-3 at 147, 1 each at 050/148/149; demote 052-ddd to appendix; resolve 134 identity |
+| G2 | 3 files with no Status header (cannot triage) — **INVESTIGATED in `docs/adr-gap-remediation-1`: only 2 genuinely lack one, both owner-gated** | CRITICAL | 147-benchmark-proof, 052-ddd-appendix, ~~134-CIR~~ | add canonical `## Status`; relocate 147-proof to `benchmarks/`; label 052-ddd as appendix — **NOTE: ADR-134-CIR DOES have a Status (`\| Status \| Proposed \|` in its header table) — mislabeled here. The two real misses (147-benchmark-proof, 052-ddd) are both inside owner-gated duplicate-number collisions (147×3, 052×2), so left untouched pending owner. The early ADRs (048/049/068/070 etc.) use `\| Status \|` not `\| **Status** \|` — different-format-but-present, not missing. Net: 0 headers added.** |
+| G3 | ~~Shipped crates cite a non-existent or wrong-identity governing ADR~~ **RESOLVED in `docs/adr-gap-remediation-1`** | CRITICAL | homecore-recorder→"ADR-132" (no file); homecore-migrate→"ADR-134" (file is CIR) | ~~write-missing-ADR (HOMECORE-RECORDER, HOMECORE-MIGRATE)~~ DONE: wrote ADR-132 (recorder, Accepted) + ADR-165 (migrate, Accepted — P1 scaffold); repointed migrate's ADR-134 refs → ADR-165 |
+| G4 | Anti-slop retractions: accuracy/security/function provably false until sweep landed | CRITICAL | 155, 154, 079, 161 (see Contradictions) | already fixed in-code by 154/155/161/162; this ledger records the retraction |
+| G5 | ~~10 streaming-engine ADRs marked `Proposed` while §Impl-Status reports Built + commits + tests~~ **RESOLVED in `docs/adr-gap-remediation-1`** | HIGH | 136–145 | ~~mark-stale → "Accepted — partial (integration glue pending)" (one batch)~~ DONE: all 10 (136–145) flipped to "Accepted — partial"; each retains its commit-pinned Implementation-Status note. NB: notes describe *building blocks built + tested*, **not** live-path integration — "partial" is the honest label, not full "Accepted" |
+| G6 | Stale `Proposed` headers on built+published code | HIGH | 029/030/031, 095/096, 152, 154–157, 024/027/072, 150 | mark-stale; reconcile with downstream/CLAUDE.md evidence |
+| G7 | Status-graph inversion: Accepted ADR depends on Proposed parent | HIGH | 032→029/030/031; 053→052; 048→045; 077→075/076; 104→103 | promote parents to match built reality, or downgrade dependents |
+| G8 | ADR-002 supersession not reciprocated by successors; 5 children stranded | HIGH | 002→016/017; children 003/007/008/009/010 | reconcile-docs (add reciprocal language or downgrade); split 002 to "partially superseded" |
+| G9 | Streaming-engine integrator crate has no governing ADR (composition/back-pressure/live-path seam) | HIGH | wifi-densepose-engine (composes 135–146) | write-missing-ADR |
+| G10 | CLAUDE.md doc-vs-header drift (doc says one status, header another) | HIGH | 017, 024, 027, 072, 152 | reconcile-docs |
+| G11 | Open security HIGH findings, gate FAILED, never marked done | HIGH | 080 (XFF bypass, leaked stack traces, JWT-in-URL CWE-598) | implement (sensing-server boundary — NOT covered by HOMECORE sweep 161/162) |
+| G12 | ADR-052→054 edge unacknowledged by successor; likely mis-modeled (impl, not replacement) | MEDIUM | 052-tauri, 054 | reconcile-docs (054 is the impl plan *for* 052, not a replacement) |
+| G13 | Capability governed only by remediation/deploy ADR, no creation/architecture ADR | MEDIUM | wasm-edge (only 160/163); occworld-candle (147 blessed Python path only); pointcloud (094 = viewer deploy only) | write-missing-ADR (taxonomy/ABI for wasm-edge; Candle backend swap; pointcloud data contract) |
+| G14 | Conflicting decisions on one topic, none superseding the others | MEDIUM | person-count 037/075/103; PQ-sign 007/109; fed key-exchange 107/108; provisioning 050/060/052; audit 010/028; RVF-WASM 009-vs-shipped | reconcile (pick one, supersede the rest) |
+| G15 | ~50 Proposed-forever chains pollute every gap analysis | MEDIUM | 003/007–010, 105–109, 118–125, HOMECORE 124–133, 033/046/049/067/074/085 | close-as-gated or mark Deferred/Rejected + open tracking issues |
+| G16 | De-facto supersessions never recorded (lifecycle graph incomplete) | MEDIUM | 098/099, 063/064, 042/153, 050/060, 035/023, 100/109, 117 retracts PyPI v1.1.0 | reconcile (add supersedes/superseded_by fields) |
+| G17 | Accepted but no implementation evidence ("unverified done") | MEDIUM | 034 (FieldView app — no crate); 044 (wifi-densepose-geo — bare Accepted, no Date/Deciders) | implement or downgrade to Proposed |
+| G18 | Workspace has ~38 crates; CLAUDE.md publishing list (12-step) and crate table (15) are stale | MEDIUM | corpus-wide (crate-graph topology) | write-missing-ADR (crate-graph / publish boundaries) + reconcile CLAUDE.md |
+
+## Supersession Integrity
+
+Only **3 formal supersession edges** exist; all three are defective (see G8/G12; full detail in `lens-findings.md` Lens 2):
+
+- **ADR-002 → ADR-016 / ADR-017** is one-directional. ADR-016 never mentions ADR-002 (its References list only 014/015); ADR-017 only *corrects* ADR-002's "fictional crate names" and never says "supersede." The census `supersedes:["ADR-002"]` on 016/017 is **file-unsupported** — the superseded ADR points up at two successors that do not point back.
+- **ADR-002 is an umbrella** whose children 003/007/008/009/010 are still `Proposed`. ADR-016/017 realize only the training/signal/MAT integration points; the RVF-container (003), PQ-crypto (007), Raft (008), WASM-edge-runtime (009), and witness-chains (010) decisions are **neither implemented nor formally superseded**. Marking the parent fully "Superseded" silently buries 5 live-but-abandoned child decisions. Recommended: split ADR-002 to "partially superseded."
+- **ADR-052-tauri → ADR-054** is declared by the predecessor but ADR-054 contains zero references to ADR-052. ADR-054 ("Full Implementation", in progress) is the impl plan *for* 052, not a replacement — likely a mis-modeled edge.
+- **No cycles** detected. The graph is clean structurally; the defect is missing reciprocity and ~7 unrecorded de-facto supersessions (G16).
+
+## Contradictions & Retractions (anti-slop centerpiece)
+
+The four CRITICAL items are the corpus's load-bearing AI-slop admissions — each an accepted-or-shipped surface whose stated accuracy/security/function was provably false until the sweep landed. **Every accuracy number predating ADR-155 should be treated as CLAIMED until re-derived through the post-155 leak-free split.** Source-cited evidence is in `lens-findings.md` Lens 3.
+
+- **[CRITICAL] ADR-155** retracts every prior NN accuracy/TTA/proof claim: real MM-Fi training validated against a *synthetic* val set with stride-1 (~99%) window leakage (§2.2); a *fake gradient* `grad += v*0.01` in the TTA path (§2.3); a *self-certifying* proof that blessed whatever the pipeline emitted and PASSed on 1e-9 float noise (§2.4).
+- **[CRITICAL] ADR-154** proves the ADR-134 CIR coherence gate was **dead in production for every canonical 56-tone frame** (`SubcarrierMismatch`, 0 Ok / 8 mismatch), silently degrading coherence to freq-only. Any "CIR-enhanced coherence/ToF" claim before this fix overstated reality.
+- **[CRITICAL] ADR-079** carries three mutually inconsistent values for its own central metric: proxy PCK@20 = 2.5% (prose) vs 35.3% (baseline table — equal to the *target*) vs 0% upper-body joints; #640 measured 0% on real local data. An Accepted ADR whose headline 10–20x improvement is self-refuting.
+- **[CRITICAL] ADR-161** fixes a HOMECORE WebSocket **auth bypass** (any non-empty token accepted) + reply-theater + no-op automation; **ADR-162** then enforces plugin Ed25519 signature verification, capability isolation, and bounded RunModes — retracting ADR-128/129/130's implied security guarantees.
+- **[HIGH]** ADR-152 self-refutes 1 of 25 claims (ESP WiFi-6 "drop-in" REFUTED 0-3); CLAUDE.md's "WiFlow-STD MEASURED-EQUIVALENT ~96% PCK" contradicts §F1's own gating (97.25% is CLAIMED until measurements (a)–(c) run). ADR-150 retracts the implied cross-subject capability (81.63% in-domain vs ~11.6% leakage-free cross-subject; DANN ~0 gain). ADR-159 ships real models but discloses person-count `training_class1_accuracy = 0.343` and renames "learned multi-person counter" → "presence detector," gutting ADR-103/104's claim.
+- **[MEDIUM]** ADR-163 leaves the ESP32/Xtensa on-hardware latency figure UNMEASURED; ADR-098↔099 partial reversal on midstream; ADR-147 self-retracts Cosmos for OccWorld.
+
+## Coverage Gaps (shipped capability, no/broken governing ADR)
+
+- ~~**CRITICAL — `homecore-recorder`** (SQLite state history + semantic search) cites "ADR-132", which **does not exist**. The durable-state backbone is ungoverned. → write HOMECORE-RECORDER ADR.~~ **RESOLVED in `docs/adr-gap-remediation-1`:** ADR-132 written (`ADR-132-homecore-recorder-history-semantic-search.md`, Status: Accepted — reverse-documented from the shipped crate).
+- ~~**CRITICAL — `homecore-migrate`** (reads untrusted Python-HA `.storage/*.json`) cites "ADR-134", but on-disk ADR-134 is CIR. A data-integrity-sensitive importer governed by a phantom identity. → resolve 134 collision + write HOMECORE-MIGRATE ADR (trust boundary).~~ **RESOLVED in `docs/adr-gap-remediation-1`:** ADR-165 written (`ADR-165-homecore-migrate-from-home-assistant.md`, Status: Accepted — P1 scaffold); crate's `ADR-134` refs repointed → ADR-165; on-disk ADR-134 (CIR) left intact. ADR-126's series-map row (which labels the *role* "ADR-134 HOMECORE-MIGRATE") is owner-gated and unchanged.
+- **HIGH — `wifi-densepose-engine`** composes ADR-135..146 onto the live 20 Hz path but **no ADR governs the integrator contract** (ordering, back-pressure, "one pipeline cycle" boundary).
+- **MEDIUM — `wasm-edge`** (~70 skills) governed only by remediation ADRs 160/163 — no creation/taxonomy/ABI ADR. **`occworld-candle`** is a Rust-native backend swap ADR-147 explicitly deferred. **`pointcloud`** has only a viewer-deploy ADR (094), no data-format contract.
+- **MEDIUM — workspace topology:** ~38 crates exist; the CLAUDE.md 15-crate table and 12-step publishing order are stale, and no ADR governs crate-graph/publish boundaries at this scale.
+- Verified-governed (scoped out): worldmodel→147, worldgraph→139, cog-*→101/103/116, ruview-swarm→148, nvsim→089/092, bfld→118-123/141, calibration→151, homecore-hap→125, geo→044, desktop→052/054.
+
+## Open / Gated Backlog (genuinely unresolved, honestly labeled)
+
+The ADR-154–163 sweep was narrowly scoped. The two largest **capability** gaps it did not touch:
+
+- **CRITICAL — Camera-teacher training validation (ADR-079 / 072 / 150).** P7–P9 Pending; blocker is a real synchronized camera+ESP32 paired-capture session + GPU training on the fleet (ruvultra RTX 5080). Cross-subject collapse (11.6%) is data-gated on a heterogeneous multi-subject CSI dataset, per ADR-150 §F3 / ADR-152 F3 (the lever is *more data*, not capacity). Accepted-on-paper, not proven.
+- **HIGH — Federation + BFLD privacy chains (ADR-105–109, 118–125).** All Proposed-only, ACs unchecked. Blockers: KIT BFId dataset (121), Pi5/Nexmon CBFR capture hardware (123 — ESP32 structurally cannot sniff CBFR), Soul-Signature + cog-ha-matter (122/125). The privacy control *plane* (ADR-141) is built; the *capture/scoring* chain it gates is not.
+- **HIGH — Sensing-server security (ADR-080).** Distinct from the HOMECORE boundary the sweep fixed; XFF bypass / stack-trace leakage / JWT-in-URL remain open.
+- **MEDIUM — gold-standard deferrals (model to follow):** ADR-163 (ESP32 on-hardware latency UNMEASURED), ADR-160 (medical/affect/weapon NOT validated, relabelled), ADR-158 (RF-through-rubble + learned counter DATA-GATED). Code is real, the claim is withheld pending absent hardware/labelled data — labels are honest.
+- **MEDIUM — purely hardware/data-gated Proposed decisions (no overreach):** ADR-023, 027, 042, 063/064, 065/066, 070, 073/078, 083, 086, 091, 103, 110 (HE-CSI needs ESP-IDF ≥5.5), 113, 114, 134/135, 143-v2, 144. *needs verification* where flags rely on downstream prose rather than direct file inspection.
+
+## Consequences
+
+**Positive.** One authoritative ledger replaces scattered, drifting status fields. The anti-slop retractions are recorded in a citable place, so the "AI slop" accusation is met with a structured admission + fix-trail rather than denial. The Gap Register is a concrete, severity-ordered work queue. Batch-fixing G5 (10 streaming-engine headers) and G1/G2 (numbering + missing headers) is high-ROI and unblocks ADR tooling.
+
+**Negative.** This ADR is a snapshot; it goes stale the moment the next ADR lands. Counts marked `~` are approximate and a few impl_state values are *needs verification* (downstream-prose-derived, not file-confirmed). Acting on the register (renumbering, status flips, supersession edits) touches ~30 files and risks transient cross-reference breakage if not done atomically.
+
+**Neutral.** No subsystem behavior changes. Renumbering decisions (which of the colliding files keeps each number) are deferred to the follow-up remediation PR — this ADR records the collision, not the resolution. Whether to close abandoned chains as `Rejected` vs `Deferred` is a judgment call left to the deciders per chain.
+
+## Links
+
+- `docs/adr/gap-analysis/census.md` — full per-ADR census (162 entries).
+- `docs/adr/gap-analysis/lens-findings.md` — five-lens findings (status-distribution, supersession-chains, contradictions, coverage-gaps, data-hardware-gated), verbatim.
+- Anti-slop sweep: ADR-154, ADR-155, ADR-156, ADR-157, ADR-158, ADR-159, ADR-160, ADR-161, ADR-162, ADR-163.
+- Most-cited defects: ADR-079, ADR-134, ADR-002, ADR-136–145, ADR-152.
+- Governance: CLAUDE.md (crate table + publishing order — stale per G18); ADR-038 (prior roadmap census, now stale).
@@ -0,0 +1,129 @@
+# ADR-165: HOMECORE-MIGRATE — Migration Tooling from Python Home Assistant
+
+| Field | Value |
+|-------|-------|
+| **Status** | Accepted — P1 scaffold (full conversion deferred to P2) |
+| **Date** | 2026-05-25 |
+| **Deciders** | ruv |
+| **Codename** | **HOMECORE-MIGRATE** |
+| **Crate** | `v2/crates/homecore-migrate` |
+| **Relates to** | [ADR-126](ADR-126-ruview-native-ha-port-master.md) (HOMECORE master — series map row "ADR-134 HOMECORE-MIGRATE"), [ADR-127](ADR-127-homecore-state-machine-rust.md) (HOMECORE-CORE), [ADR-132](ADR-132-homecore-recorder-history-semantic-search.md) (HOMECORE-RECORDER — P2 side-by-side export target) |
+| **Tracking issue** | [#800](https://github.com/ruvnet/RuView/pull/800) (HOMECORE intake) |
+
+> **Number-collision resolution (2026-06-12).** The HOMECORE series in ADR-126 §4 planned
+> "ADR-134 = HOMECORE-MIGRATE", and the `homecore-migrate` crate cites "ADR-134" throughout.
+> But the on-disk `ADR-134-csi-to-cir-time-domain-multipath.md` is a **different, unrelated
+> decision** (First-Class CIR Support, a signal-processing tier). The migrate crate was
+> therefore governed by a phantom identity (ADR-164 Gap G3 / Coverage-Gaps Lens §A). This
+> ADR takes the next free number (**165**) and becomes the real governing record for
+> HOMECORE-MIGRATE; the `ADR-134` references inside `v2/crates/homecore-migrate/` are
+> repointed to ADR-165. The real ADR-134 (CIR) is untouched. ADR-126's series-map row still
+> labels the *role* "ADR-134 HOMECORE-MIGRATE" for historical traceability; that registry
+> renumber is owner-gated and left for the follow-up. This ADR reverse-documents the shipped
+> P1 scaffold; it introduces no new design.
+
+---
+
+## 1. Context
+
+ADR-126 decided to reimplement Home Assistant (HA) natively in Rust. A user adopting
+HOMECORE has an existing HA install whose configuration lives in two places on disk:
+
+- `.storage/*.json` — versioned JSON envelopes (`{ version, minor_version, data }`) holding
+  the entity registry, device registry, and config entries;
+- top-level YAML — `secrets.yaml`, `automations.yaml`.
+
+To migrate, HOMECORE must read this foreign, **untrusted** on-disk state. It is untrusted in
+the security sense: the schema can drift between HA releases, and silently mis-parsing a
+registry would corrupt the imported home. ADR-164 flagged this as a CRITICAL coverage gap —
+a data-integrity-sensitive importer governed by a non-existent ADR identity.
+
+The decision an ADR must pin here is the **trust boundary and import contract**: which HA
+files are read, how schema versions are validated, and what happens on an unknown version.
+
+## 2. Decision
+
+Ship `homecore-migrate` as a CLI + library that reads an existing HA filesystem and imports
+its configuration into HOMECORE. P1 is a **scaffold**: it parses and inspects everything and
+converts the entity registry; full conversion of the remaining artifacts is deferred to P2.
+
+### 2.1 Storage reader + versioned format gate (P1, shipped)
+
+- `HaStorageDir` / `HaStorageEnvelope` read HA's `.storage/` directory; `read_envelope(path)`
+  deserializes a `.storage/*.json` envelope (`src/storage.rs`).
+- Versioned parsers live under `storage_format::v<N>` (e.g. `v13` for the entity registry)
+  (`src/storage_format/`).
+- **Schema-version validation is the load-bearing safety rule (§6 Q5 of this ADR):** an
+  unknown `minor_version` is a **hard error** (`MigrateError::UnsupportedSchemaVersion`),
+  never a silent best-effort parse. Better to refuse than to corrupt.
+
+### 2.2 Per-artifact parsers (P1, shipped)
+
+- `entity_registry::load()` — `core.entity_registry` → `Vec<homecore::EntityEntry>`
+  (ready for import).
+- `device_registry::load()` — `core.device_registry` → `Vec<DeviceImport>` (P1 diagnostic;
+  full conversion P2).
+- `config_entries::load()` — `core.config_entries` → domain counts + integration names
+  (the format is undocumented per §6 Q5; treated diagnostically).
+- `secrets::load_secrets()` — `secrets.yaml` → `HashMap<String, String>` (resolution P2).
+- `automations::load()` — `automations.yaml` → count + ID/alias list (conversion P2).
+
+### 2.3 CLI (P1, shipped)
+
+- `homecore-migrate inspect <ha-dir>` previews what will be migrated (entity/device/config
+  counts, redacted secret/automation lists) (`src/cli.rs`, `src/main.rs`).
+- `import-entities` and `export-for-sidecar` are declared but their full behaviour is P2.
+
+### 2.4 Structured errors (P1, shipped)
+
+- `MigrateError` carries context (`path`, line/field) for I/O, JSON, YAML, missing-field,
+  unsupported-schema-version, and entity-id parse failures (`src/lib.rs`).
+
+### 2.5 Deferred to P2+ (NOT built — honestly labelled)
+
+- Convert `config_entries` → HOMECORE plugin manifests.
+- Convert `automations.yaml` → `homecore-automation` YAML.
+- Side-by-side runtime mode (requires `homecore-recorder`, ADR-132; behind the `recorder`
+  Cargo feature, currently a no-op stub).
+- `!secret` reference resolution in non-secrets YAML files.
+
+### 2.6 Test evidence (as shipped)
+
+- 19 tests (`cargo test -p homecore-migrate`), per the crate README badge.
+
+## 3. Consequences
+
+**Positive.**
+
+- The trust boundary is explicit: unknown HA schema versions are rejected, not guessed, so a
+  schema drift fails loudly instead of corrupting an imported home.
+- Reusing HA's own `.storage` and YAML formats means no intermediate export step; the tool
+  reads a live HA install directly.
+- P1 `inspect` gives users a no-risk dry run before any write.
+
+**Negative / honest limits.**
+
+- P1 is a **scaffold**: only the entity registry is conversion-ready. Device registry,
+  config-entry→plugin, automation, and secret-resolution conversions are P2 and **not yet
+  built** — the Status field and crate docs say so.
+- The side-by-side recorder export depends on ADR-132 and is currently a feature-gated
+  no-op.
+- Performance figures in the README (envelope parse < 5 ms, 1 000-entity load < 50 ms) are
+  estimates, **needs verification** with a benchmark.
+
+**Neutral.**
+
+- This resolves only the *identity* of the migrate decision (134→165). The broader 6-way
+  duplicate-number cleanup (incl. ADR-126's series-map registry row) is owner-gated.
+
+## 4. Links
+
+- Crate: `v2/crates/homecore-migrate/` — `Cargo.toml`, `README.md`, `src/lib.rs`,
+  `src/storage.rs`, `src/storage_format/`, `src/entity_registry.rs`,
+  `src/device_registry.rs`, `src/config_entries.rs`, `src/secrets.rs`,
+  `src/automations.rs`, `src/cli.rs`, `src/main.rs`.
+- [ADR-126](ADR-126-ruview-native-ha-port-master.md) — HOMECORE master (series map: HOMECORE-MIGRATE).
+- [ADR-132](ADR-132-homecore-recorder-history-semantic-search.md) — HOMECORE-RECORDER (P2 side-by-side export target).
+- [ADR-134](ADR-134-csi-to-cir-time-domain-multipath.md) — First-Class CIR Support (the *unrelated* decision the crate was mistakenly citing).
+- [ADR-164](ADR-164-adr-corpus-gap-analysis.md) — gap analysis that surfaced this collision (Gap G3).
+- [Home Assistant `.storage` format](https://developers.home-assistant.io/docs/storage/).
@@ -0,0 +1,168 @@
+# ADR Corpus Census
+
+Full per-ADR census underpinning ADR-164. **162 ADR entries across 156 distinct files** (6 duplicate-number collisions). Source of truth for the gap-analysis lenses. Where the census is uncertain it is marked *needs verification*.
+
+| ADR | Title | Status | impl_state | Flags |
+|-----|-------|--------|-----------|-------|
+| ADR-001 | WiFi-Mat Disaster Detection Architecture | Accepted | implemented | data/hardware-gated (rubble-penetration unproven without field hardware) |
+| ADR-002 | RuVector RVF Integration Strategy | Superseded by ADR-016 + ADR-017 | superseded | umbrella ADR; child ADRs 003/007/008/009/010 still Proposed |
+| ADR-003 | RVF Cognitive Containers for CSI Data | Proposed | proposed-only | proposed-but-looks-abandoned (parent 002 superseded, never advanced) |
+| ADR-004 | HNSW Vector Search for Signal Fingerprinting | Partially realized by ADR-024; extended by ADR-027 | partial | realized indirectly via downstream ADRs, not directly |
+| ADR-005 | SONA Self-Learning Pose Estimation | Partially realized in ADR-023; extended by ADR-027 | partial | realized indirectly via ADR-023 (MicroLoRA/EWC++) |
+| ADR-006 | GNN-Enhanced CSI Pattern Recognition | Partially realized in ADR-023; extended by ADR-027 | partial | realized indirectly via ADR-023 (2-layer GCN), scope narrowed |
+| ADR-007 | Post-Quantum Cryptography for Secure Sensing | Proposed | proposed-only | proposed-but-looks-abandoned (parent 002 superseded) |
+| ADR-008 | Distributed Consensus for Multi-AP | Proposed | proposed-only | proposed-but-looks-abandoned (parent 002 superseded) |
+| ADR-009 | RVF WASM Runtime for Edge Deployment | Proposed | proposed-only | contradicts shipped wifi-densepose-wasm crate it proposes to replace |
+| ADR-010 | Witness Chains for Audit-Trail Integrity | Proposed | proposed-only | witness-bundle (ADR-028) fills this role instead |
+| ADR-011 | Python Proof-of-Reality / Mock Elimination | Proposed (URGENT) | partial | proof pipeline (verify.py/ADR-028) live despite Proposed status; credibility-gated |
+| ADR-012 | ESP32 CSI Sensor Mesh | Accepted — Partially Implemented | partial | hardware-gated; mesh partial, single-node firmware working per ADR-018 |
+| ADR-013 | Feature-Level Sensing on Commodity Gear | Accepted — Implemented (36/36 tests) | implemented | — |
+| ADR-014 | SOTA Signal Processing | Accepted | implemented | — |
+| ADR-015 | Public Dataset Training Strategy | Accepted | implemented | data-gated (MM-Fi/Wi-Pose availability/licensing) |
+| ADR-016 | RuVector Training-Pipeline Integration | Accepted | implemented | supersedes ADR-002 (but file never mentions 002 — unsupported claim) |
+| ADR-017 | RuVector Signal + MAT Integration | Accepted | implemented | CLAUDE.md still lists as Proposed; supersedes 002 only via "Correction" prose |
+| ADR-018 | ESP32 Dev Implementation | Proposed | partial | status stale — ADR-012 cites it as working firmware/aggregator |
+| ADR-019 | Sensing-Only UI Mode with Gaussian Splat Viz | Accepted | implemented | status in table format not ## header |
+| ADR-020 | Migrate AI/Model Inference to Rust (RuVector + ONNX) | Accepted | partial | table-format status; overlaps ADR-019 backend-decoupling scope |
+| ADR-021 | Vital Sign Detection via rvdna Pipeline | Partially Implemented | partial | wifi-densepose-vitals crate exists |
+| ADR-022 | Enhanced Windows WiFi Fidelity via Multi-BSSID | Partially Implemented | partial | wifi-densepose-wifiscan crate exists |
+| ADR-023 | Trained DensePose Model w/ RuVector Signal Intelligence | Proposed | proposed-only | data/hardware-gated; scaffold w/ random weights |
+| ADR-024 | Project AETHER — Contrastive CSI Embedding | Proposed | proposed-only | CLAUDE.md lists Accepted; pose_tracker.rs uses AETHER re-ID — contradiction |
+| ADR-025 | macOS CoreWLAN WiFi Sensing (ORCA) | Proposed | proposed-only | hardware-gated (Mac Mini M2 Pro); RSSI-only |
+| ADR-026 | Survivor Track Lifecycle Management (MAT) | Accepted | implemented | explicit Supersedes: None |
+| ADR-027 | Project MERIDIAN — Cross-Env Domain Generalization | Proposed | proposed-only | CLAUDE.md lists Accepted — contradiction; data-gated |
+| ADR-028 | ESP32 Capability Audit & Witness Record | Accepted | implemented | audit/witness record; pins commit 96b01008 |
+| ADR-029 | RuvSense — Sensing-First RF Multistatic Mode | Proposed | stale-or-contradicted | repo has ruvsense/ (16 modules); ADR-032 hardens it |
+| ADR-030 | RuvSense Persistent Field Model | Proposed | stale-or-contradicted | field_model/longitudinal/cross_room modules exist; ADR-032 secures |
+| ADR-031 | RuView — Cross-Viewpoint Fusion | Proposed | stale-or-contradicted | ruvector/src/viewpoint/ exists; near-duplicate of ADR-029 |
+| ADR-032 | Multistatic Mesh Security Hardening | Accepted | implemented | hardens Proposed 029/030/031 — status-graph inversion |
+| ADR-033 | CRV Signal Line Sensing (Coordinate Remote Viewing) | Proposed | proposed-only | speculative/metaphor-driven; abandonment risk |
+| ADR-034 | Expo React Native Mobile App (FieldView) | Accepted | unknown | no mobile-app crate/dir in CLAUDE.md — unverified |
+| ADR-035 | Live Sensing UI Accuracy & Data Source Transparency | Accepted | implemented | bug-fix; heuristic pose superseded in spirit by 023/036 |
+| ADR-036 | RVF Model Training Pipeline & UI Integration | Proposed | proposed-only | overlaps ADR-023 scope |
+| ADR-037 | Multi-Person Pose from Single ESP32 CSI Stream | Proposed | proposed-only | explicit Supersedes: None; HW limitation noted |
+| ADR-038 | Sublinear GOAP for Roadmap Optimization | Proposed | proposed-only | meta/process ADR; own corpus census may be stale |
+| ADR-039 | ESP32-S3 Edge Intelligence Pipeline | Accepted (hardware-validated) | implemented | hardware-validated |
+| ADR-040 | WASM Programmable Sensing (Tier 3) | Accepted | implemented | depends on ADR-039; WASM3 optional |
+| ADR-041 | WASM Module Collection — Sensing Registry | Accepted (Phase 1) | partial | ~57 modules catalog/proposed; exotic modules speculative |
+| ADR-042 | Coherent Human Channel Imaging (CHCI) | Proposed | proposed-only | hardware-gated (custom PCB/TCXO); superseded-in-intent by ADR-153 |
+| ADR-043 | Sensing Server UI API Completion | Accepted | implemented | internal route count contradiction (14 vs 17) |
+| ADR-044 | Geospatial Satellite Integration | Accepted | unknown | no Date/Deciders; wifi-densepose-geo crate not in CLAUDE.md table |
+| ADR-045 | AMOLED Display Support for ESP32-S3 | Proposed | proposed-only | hardware-gated (LilyGO T-Display-S3); ADR-048 depends on it |
+| ADR-046 | Android TV Box / Armbian Deployment Target | Proposed | proposed-only | proposed-but-looks-abandoned; Phase 2 speculative |
+| ADR-047 | RuView Observatory — Three.js Visualization | Accepted (Implemented) | implemented | — |
+| ADR-048 | Adaptive CSI Activity Classifier | Accepted | implemented | depends on Proposed ADR-045 |
+| ADR-049 | Cross-Platform WiFi Detection & Graceful Degradation | Proposed | proposed-only | targets Python v1 legacy; abandonment risk |
+| ADR-050 | Provisioning Tool Enhancements | Proposed | partial | DUPLICATE NUMBER; partially fulfilled by ADR-060 |
+| ADR-050 | Quality Engineering Response — Security Hardening | Accepted | partial | DUPLICATE NUMBER; unverified claims (54K fps); findings #6-8 unconfirmed |
+| ADR-052 | DDD Bounded Contexts (appendix) | (none — appendix, no Status) | unknown | missing-status; DUPLICATE NUMBER; cross-ref errors (cites 044 for provisioning) |
+| ADR-052 | Tauri Desktop Frontend — Hardware Mgmt & Viz | Proposed | partial | DUPLICATE NUMBER; superseded_by ADR-054; status drift |
+| ADR-053 | UI Design System — Dark Professional | Accepted | implemented | depends on Proposed ADR-052 |
+| ADR-054 | RuView Desktop Full Implementation | Accepted — in progress | partial | command matrix mostly Stub; espflash version drift vs 052 |
+| ADR-055 | Integrated Sensing Server in Desktop App | Accepted | implemented | — |
+| ADR-056 | RuView Desktop Complete Capabilities Reference | Accepted | partial | reference doc; "complete" overstates impl state |
+| ADR-057 | Firmware CSI Build Guard & sdkconfig.defaults | Accepted | implemented | minor C6 CSI matrix tension vs CLAUDE.md |
+| ADR-058 | Dual-Modal WASM Browser Pose (Video + CSI) | Proposed | partial | data-gated; ships placeholder weights |
+| ADR-059 | Live ESP32 CSI Pipeline Integration | Accepted | implemented | hardware-gated (physical ESP32-S3 + UDP:5005) |
+| ADR-060 | Provision Channel Override & MAC Filtering | Accepted | implemented | fulfills part of Proposed ADR-050(prov) without superseding |
+| ADR-061 | QEMU ESP32-S3 Emulation for Firmware Testing | Accepted | implemented | RF-PHY paths untestable in QEMU |
+| ADR-062 | QEMU ESP32-S3 Swarm Configurator | Accepted | implemented | — |
+| ADR-063 | 60 GHz mmWave Sensor Fusion with WiFi CSI | Proposed | proposed-only | hardware-gated (ESP32-C6+MR60BHA2); superseded-in-scope by 064 |
+| ADR-064 | Multimodal Ambient Intelligence (CSI+mmWave+env) | Proposed | proposed-only | hardware-gated; mixes build-now + speculative tiers |
+| ADR-065 | Hotel Guest Happiness Scoring | Proposed | proposed-only | hardware-gated (Cognitum Seed Pi Zero 2 W) |
+| ADR-066 | ESP32 CSI Swarm with Cognitum Seed Coordinator | Proposed | proposed-only | hardware-gated; overlaps 068/069 |
+| ADR-067 | RuVector v2.0.4→v2.0.5 Upgrade | Proposed | proposed-only | CLAUDE.md still v2.0.4 — not adopted |
+| ADR-068 | Per-Node State Pipeline for Multi-Node Sensing | Accepted | implemented | — |
+| ADR-069 | ESP32 CSI → Cognitum Seed RVF Ingest Pipeline | Accepted | implemented | hardware-gated (live Cognitum Seed fw v0.8.1) |
+| ADR-070 | Self-Supervised Pretraining from Live CSI + Seed | Accepted | partial | hardware-gated (live 2-node + Seed capture) |
+| ADR-071 | ruvllm Training Pipeline for CSI Models | Proposed | proposed-only | overlaps 072/079 + libtorch pipeline |
+| ADR-072 | WiFlow Pose Estimation Architecture | Proposed | partial | data-gated; referenced as implemented in CLAUDE.md (WiFlow-STD) — stale header |
+| ADR-073 | Multi-Frequency Mesh Scanning | Proposed | proposed-only | hardware-gated (2-node multi-AP) |
+| ADR-074 | Spiking Neural Network for CSI Sensing | Proposed | proposed-only | proposed-but-looks-abandoned (no in-repo SNN signal) |
+| ADR-075 | Min-Cut Person Separation from Subcarrier Corr | Proposed | proposed-only | fixes #348; 077/078 depend on it though Proposed |
+| ADR-076 | CSI Spectrogram Embeddings via CNN + Graph Transformer | Proposed | proposed-only | — |
+| ADR-077 | Novel RF Sensing Applications | Accepted | partial | depends on Proposed 075/076; data-gated |
+| ADR-078 | Multi-Frequency Mesh Sensing Applications | Proposed | proposed-only | hardware-gated; depends on Proposed 073 |
+| ADR-079 | Camera Ground-Truth Training Pipeline | Accepted | partial | P7-P9 Pending; internal PCK contradiction (2.5% vs 35.3% vs 0%); #640 = 0% |
+| ADR-080 | QE Analysis Remediation Plan | Proposed | proposed-only | unfixed security HIGH findings (XFF bypass, stack traces, JWT-in-URL) |
+| ADR-081 | Adaptive CSI Mesh Firmware Kernel | Accepted — L1-5 host-tested | partial | mesh RX + Ed25519 signing deferred to Phase 3.5 |
+| ADR-082 | Pose Tracker Confirmed-Track Output Filter | Accepted — implemented | implemented | fixes #420 |
+| ADR-083 | Per-Cluster Pi Compute Hop | Proposed — pending field evidence | proposed-only | hardware-gated (status explicitly pending field evidence) |
+| ADR-084 | RaBitQ Similarity Sensor (4 pipeline points) | Accepted — merged PR #435 | implemented | acceptance on synthetic data; <1pp regression deferred to soak |
+| ADR-085 | RaBitQ Similarity Sensor — Pipeline Expansion (7 sites) | Proposed | proposed-only | proposed-but-looks-abandoned (refines 084, never advanced) |
+| ADR-086 | Edge Novelty Gate — RaBitQ on Sensor MCU | Proposed | proposed-only | hardware-gated (no_std port + real-deployment suppression rates) |
+| ADR-089 | nvsim — NV-Diamond Magnetometer Simulator | Accepted — Passes 1-5 merged | partial | Pass 6 (proof bundle + bench) pending |
+| ADR-090 | nvsim — Full Hamiltonian/Lindblad Solver | Proposed — conditional | proposed-only | explicitly deferred decision-to-defer |
+| ADR-091 | Stand-off Radar — 77 GHz / sub-THz Research | Proposed — research only | proposed-only | hardware-gated (COTS sub-THz); ITAR/dual-use |
+| ADR-092 | nvsim Dashboard — Vite + Dual-Transport | Implemented (2026-04-27) | implemented | 4/12 gates need external infra; PR #436 open |
+| ADR-093 | nvsim Dashboard Gap Analysis | Implemented (2026-04-27) | implemented | P2.7/P2.8 polish deferred |
+| ADR-094 | Live 3D Point Cloud Viewer — GH Pages | Proposed (2026-04-29) | proposed-only | governs viewer deploy only, not crate data contract |
+| ADR-095 | rvCSI — Edge RF Sensing Runtime Platform | Proposed | implemented | header stale — ADR-097 confirms built, published 0.3.1 |
+| ADR-096 | rvCSI — Crate Topology, napi-c Shim, napi-rs | Proposed | implemented | header stale — 9 crates published 0.3.1 |
+| ADR-097 | Adopt rvCSI as RuView's primary CSI runtime | Proposed | proposed-only | RuView vendors but does not yet consume — adoption open |
+| ADR-098 | Evaluate ruvnet/midstream | Rejected (with carve-outs) | proposed-only | rejection; carve-outs revived by ADR-099 |
+| ADR-099 | Adopt midstream — introspection + low-latency tap | Proposed | proposed-only | tension with ADR-098 (which rejected midstream) |
+| ADR-100 | Cognitum Cog Packaging Specification | Accepted | implemented | first cog shipped 2026-05-19 (ADR-101) |
+| ADR-101 | Pose Estimation Cog (WiFi-DensePose side) | Accepted — v0.0.1 shipped | implemented | hardware-gated; signed binaries on GCS |
+| ADR-102 | Edge Module Registry Integration | Accepted | implemented | serves 105-cog catalog |
+| ADR-103 | Learned Multi-Person Counter (cog-person-count) | Proposed | proposed-only | data/hardware-gated; claim gutted by ADR-159 |
+| ADR-104 | RuView MCP Server + CLI Distribution | Accepted | partial | depends on Proposed ADR-103 for count tool |
+| ADR-105 | Federated learning for RuView CSI personalization | Proposed | proposed-only | head of 105-108 chain, none implemented |
+| ADR-106 | Differential privacy + biometric isolation | Proposed | proposed-only | extends Proposed 105 |
+| ADR-107 | Cross-installation federation w/ secure aggregation | Proposed | proposed-only | classical DH later superseded by 108 |
+| ADR-108 | Kyber PQ key exchange for federation | Proposed | proposed-only | extends Proposed 107 (parent unimplemented) |
+| ADR-109 | Dilithium PQ signatures for cog distribution | Proposed | proposed-only | extends ADR-100; sister of 108 |
+| ADR-110 | ESP32-C6 firmware extension (Wi-Fi 6 CSI, 802.15.4, TWT, LP) | Accepted — P1-P10 complete v0.7.0 | implemented | HE-CSI needs ESP-IDF ≥5.5 (v5.4 downconverts to HT) |
+| ADR-113 | Multistatic anchor placement strategy | Proposed | proposed-only | amends ADR-029; simulation-derived not HW-validated |
+| ADR-114 | cog-quantum-vitals | Proposed | proposed-only | hardware-gated (nvsim today, real NV-diamond in prod); R13 NEGATIVE |
+| ADR-115 | Home Assistant via MQTT auto-discovery + Matter bridge | Accepted (MQTT) / Proposed (Matter) | partial | mixed status; Matter deferred to v0.7.1 |
+| ADR-116 | HA + Matter as a Cognitum Seed cog (cog-ha-matter) | Proposed — P2 scaffold compiles | partial | provisional; Matter deferred to v0.8 |
+| ADR-117 | pip wifi-densepose via PyO3 + maturin | Proposed | proposed-only | current PyPI v1.1.0 stale; tracking issue TBD |
+| ADR-118 | BFLD — Beamforming Feedback Layer for Detection | Proposed | proposed-only | umbrella; sub-ADRs 119-123 |
+| ADR-119 | BFLD Frame Format and Wire Protocol | Proposed | proposed-only | child of Proposed 118 |
+| ADR-120 | BFLD Privacy Class and Hash Rotation | Proposed | proposed-only | child of Proposed 118 |
+| ADR-121 | BFLD Identity Risk Scoring and Coherence Gate | Proposed | proposed-only | abandonment risk; data-gated (KIT BFId dataset) |
+| ADR-122 | BFLD RuView Surface — HA/Matter/MQTT | Proposed | proposed-only | abandonment risk; depends on Soul Signature + cog-ha-matter |
+| ADR-123 | BFLD Capture Path — Pi5/Nexmon, ESP32 feasibility | Proposed | proposed-only | hardware-gated (ESP32 cannot sniff CBFR) |
+| ADR-124 | rvagent — MCP + ruvector npm lib (SENSE-BRIDGE) | Proposed | proposed-only | abandonment risk; not published; open questions |
+| ADR-125 | RuView ↔ Apple Home native HAP bridge | Proposed | proposed-only | abandonment risk; hardware-gated (same-L2 pairing) |
+| ADR-126 | HOMECORE — Rust+WASM+TS port of Home Assistant | Proposed | proposed-only | multi-quarter; series map cites missing 131/132 + mis-numbered 134 |
+| ADR-127 | HOMECORE-CORE — state machine, registries, event bus | Proposed | proposed-only | future-dated Q3 2026 |
+| ADR-128 | HOMECORE-PLUGINS — WASM integration plugin system | Proposed | proposed-only | future-dated; depends on 127 ABI freeze |
+| ADR-129 | HOMECORE-AUTO — automation engine + template eval | Proposed | proposed-only | future-dated; broken cross-ref to ADR-134 |
+| ADR-130 | HOMECORE-API — wire-compatible REST + WS | Proposed | proposed-only | future-dated; wire-compat needs HA companion-app suite |
+| ADR-133 | HOMECORE-ASSIST — voice/intent + Ruflo bridge | Proposed | partial | missing tracking issue; P1 partial build, P2 deferred |
+| ADR-134 | First-Class Channel Impulse Response (CIR) Support | Proposed | proposed-only | DUPLICATE IDENTITY (126/129 cite 134 as HOMECORE-MIGRATE); hardware-gated |
+| ADR-135 | Empty-Room Baseline Calibration | Proposed | proposed-only | hardware-gated (COM9/COM12 + 802.15.4 sync) |
+| ADR-136 | RuView Rust Streaming Engine — Architecture/Contracts | Proposed | partial | status-contradiction: §8 says Built (commit 11f89727f, 9 tests) |
+| ADR-137 | Fusion Engine Quality Scoring | Proposed | partial | status-contradiction: Built (commit 4fa3847ac, 6 tests) |
+| ADR-138 | WiFi-7 MLO LinkGroup + ArrayCoordinator gating | Proposed | partial | status-contradiction: Built (commit fc7674bde, 8 tests) |
+| ADR-139 | WorldGraph — Environmental Digital Twin | Proposed | partial | status-contradiction: Built (commit 521a012d8, 7 tests) |
+| ADR-140 | Semantic State Record + Ruflo Agent Bridge | Proposed | partial | status-contradiction: Built (commit 169a355bd, 4 tests); Rest kind not built |
+| ADR-141 | BFLD Privacy Control Plane | Proposed | partial | header stale vs Implementation note (commit 7d88eb84c, 6 tests) |
+| ADR-142 | Evolution Tracker + Temporal VoxelMap | Proposed | partial | header stale vs note (commit 1f8e180d6, 6 tests) |
+| ADR-143 | RF SLAM v2 — Reflector Discovery + Anchor Learning | Proposed | partial | header stale (commit 2d4f3dea5); v2 dormant behind 7-day validation |
+| ADR-144 | UWB Range-Constraint Fusion | Proposed | partial | header stale (commit b10bc2e9a); no UWB radio in fleet |
+| ADR-145 | Ablation Evaluation Harness | Proposed | partial | referenced as existing by 149/150/151; F4/UWB variant HW-gated |
+| ADR-146 | RF Encoder Multi-Task Heads + Uncertainty | Proposed | proposed-only | no Impl note (unlike 141-144); depends on tch/libtorch |
+| ADR-147 | adam-mode — light theme toggle | Proposed | proposed-only | DUPLICATE NUMBER (3 files); referenced as landed by 148-yoga |
+| ADR-147 | Occupancy World Model (OccWorld/RoboOccWorld) | Accepted | partial | DUPLICATE NUMBER; self-revised from Cosmos; Phase B gated |
+| ADR-147 | Benchmark Proof — OccWorld on RTX 5080 | (none) | unknown | MISSING STATUS; DUPLICATE NUMBER; baseline-without-fine-tuning (random weights) |
+| ADR-148 | Drone Swarm Control System | In Progress | partial | DUPLICATE NUMBER; re-routes 147 Cosmos item to 149 |
+| ADR-148 | yoga-mode — pose detection/scoring demo | Proposed | proposed-only | DUPLICATE NUMBER; no tracking issue |
+| ADR-149 | AetherArena — Spatial-Intelligence Benchmark (HF) | Accepted | partial | DUPLICATE NUMBER; external repo out-of-tree; Wi-Pose dropped |
+| ADR-149 | Drone Swarm Benchmarking Methodology | Accepted (peer-reviewed) | partial | DUPLICATE NUMBER; critiques 148's own numbers |
+| ADR-150 | RuView RF Foundation Encoder | Proposed | partial | status Proposed but cites measured 81.63% in-domain vs ~11.6% cross-subject |
+| ADR-151 | Per-Room Calibration & Specialized Model Training | Accepted — Stages 1-5 impl | partial | HF-backbone distillation pending |
+| ADR-152 | WiFi-Pose SOTA 2026 Intake | Proposed | partial | header stale; §2.1-2.3/2.6 impl, WiFlow-STD ~96% PCK; 1/25 claim REFUTED |
+| ADR-153 | IEEE 802.11bf-2025 Forward-Compat Protocol Model | accepted | implemented | amends ADR-152 §2.4; OTA/silicon binding deferred |
+| ADR-154 | Signal/DSP Beyond-SOTA Sweep — M0 | Proposed | partial | header likely stale; discloses dead CIR coherence gate; ~45 deferred |
+| ADR-155 | NN/Training Beyond-SOTA Sweep — M1 | Proposed | partial | header likely stale; retracts synthetic-val/fake-gradient/self-cert proof |
+| ADR-156 | RuVector/Cross-Viewpoint Fusion Sweep — M2 | Proposed | partial | header likely stale; one staged finding is numeric no-op |
+| ADR-157 | Hardware/Sensing-Acquisition Sweep — M3 | Proposed | partial | header likely stale; headline negative result (layer already hardened) |
+| ADR-158 | MAT/World-Model Cluster Sweep — Anti-AI-Slop | accepted | implemented | life-safety; fixes triage inflation; some paths DATA-GATED |
+| ADR-159 | Cognitum Appliance Cluster Sweep — Anti-AI-Slop | accepted | implemented | person-count training_class1_accuracy = 0.343; description renamed |
+| ADR-160 | Edge Skill Library (wasm-edge) — Honest Labeling | accepted | implemented | medical/affect/weapon NOT validated — relabelled |
+| ADR-161 | HOMECORE Server — WS Auth Bypass, Reply-Theater | accepted | implemented | CRITICAL WS auth bypass fix; amends 130/129/128 |
+| ADR-162 | HOMECORE Plugin Security + Bounded RunModes | accepted | implemented | security-critical; enforces ADR-161 deferrals |
+| ADR-163 | Edge-Latency Measurement — CLAIMED→MEASURED | accepted | implemented | ESP32/Xtensa figure remains UNMEASURED (hardware-gated) |
@@ -0,0 +1,316 @@
+# ADR Corpus Gap Analysis — Five-Lens Findings
+
+Research notes backing ADR-164. Each lens output is reproduced verbatim. Census: 162 ADR entries across 156 distinct files (6 duplicate-number collisions verified on disk).
+
+---
+
+## Lens 1: status-distribution
+
+Confirmed: ADR-147-benchmark-proof.md and ADR-134-csi-to-cir have no `Status` line in their headers (the 052-ddd hits are Rust code in the body, not a header; the ADR-052 appendix lacks a real Status header per its first lines). Findings are evidence-grounded. Final analysis below.
+
+### ADR Corpus — Status & Implementation Distribution
+
+Census: **162 ADR entries** across **156 distinct files** (6 duplicate-number collisions verified on disk).
+
+#### Status tally
+
+| Status bucket | Count |
+|---|---|
+| Accepted (incl. "Accepted — partial/in-progress/Phase 1" variants) | ~56 |
+| Proposed (incl. "Proposed — conditional/research-only") | ~88 |
+| Superseded | 1 (ADR-002) |
+| Rejected | 1 (ADR-098) |
+| Missing / no Status header | 3 (ADR-147-benchmark-proof, ADR-052-ddd appendix, ADR-134-CIR) |
+| Mixed/dual status in one ADR | 3 (ADR-115, ADR-149-AetherArena vs swarm, ADR-133) |
+
+#### impl_state tally
+
+| impl_state | Count |
+|---|---|
+| implemented | ~36 |
+| partial | ~50 |
+| proposed-only | ~64 |
+| stale-or-contradicted | 3 (ADR-029, 030, 031) |
+| unknown | 5 (ADR-034, 044, 052-ddd, 147-proof, …) |
+| superseded | 1 (ADR-002) |
+
+**Headline:** ~114 of 162 ADRs (70%) are decisions that never fully landed (proposed-only + partial + stale + unknown). The dominant failure mode is **stale Status headers** — Accepted/implemented work still labeled "Proposed."
+
+#### SEVERITY: CRITICAL — Status header missing or structurally absent (cannot triage)
+
+- **ADR-147-benchmark-proof.md** — *No `Status` header at all* (grep confirmed). Not a true ADR; it's a benchmark artifact (OccWorld @ ~213ms on RTX 5080, random weights) misfiled under the ADR-147 number. **Action: relocate to `docs/proof/` or `benchmarks/`, remove ADR number.**
+- **ADR-134-csi-to-cir-time-domain-multipath.md** — *No `Status` header* (grep confirmed) in the header region. Body says Proposed but the field is not in canonical position. Compounded by a **number collision**: ADR-126/129 reference "ADR-134" as HOMECORE-MIGRATE, but the on-disk file is CIR. **Action: add canonical `## Status` line; resolve the 134 identity split.**
+- **ADR-052-ddd-bounded-contexts.md** — Appendix doc with no Status/Date header (grep found only Rust code, no header field). **Action: mark explicitly "Appendix to ADR-052 (no independent status)".**
+
+#### SEVERITY: CRITICAL — Duplicate ADR numbers (6 collisions, all verified on disk)
+
+| Number | Colliding files | Action |
+|---|---|---|
+| **147** | adam-mode-light-theme · nvidia-cosmos/OccWorld · benchmark-proof | Renumber 2 of 3 |
+| **148** | drone-swarm-control-system · yoga-mode-pose-system | Renumber 1 |
+| **149** | AetherArena-leaderboard · swarm-benchmarking | Renumber 1 |
+| **050** | provisioning-tool-enhancements · quality-engineering-security-hardening | Renumber 1 |
+| **052** | tauri-desktop-frontend · ddd-bounded-contexts (appendix) | Demote appendix |
+| **134** | csi-to-cir (on disk) · HOMECORE-MIGRATE (referenced, no file) | Resolve identity |
+
+These break the ADR index and `/adr` tooling — two ADRs answering to one number is a corpus-integrity defect, not cosmetics.
+
+#### SEVERITY: HIGH — Status header stale vs. shipped reality (Proposed header on landed code)
+
+These are the most dangerous: an auditor reading the header concludes "not built" when code + tests exist. Ranked by blast radius:
+
+1. **ADR-136 → ADR-145** (streaming-engine series, 10 ADRs) — every header says `Proposed` but each `§ Implementation Status` reports **"Built" with pinned commits + passing tests** (136: 11f89727f; 137: 4fa3847ac; 138: fc7674bde; 139: 521a012d8; 140: 169a355bd; 141: 7d88eb84c; 142: 1f8e180d6; 143: 2d4f3dea5; 144: b10bc2e9a; 145 referenced as landed by 149/150/151). **Bulk action: flip headers to "Accepted — partial (integration glue pending)".**
+2. **ADR-029 / 030 / 031** (RuvSense/field-model/cross-viewpoint) — `Proposed` but repo has `signal/src/ruvsense/` (16 modules) and `ruvector/src/viewpoint/`, and **Accepted ADR-032 hardens them** — an Accepted ADR depending on Proposed parents (status-graph inversion).
+3. **ADR-095 / 096** (rvCSI) — `Proposed` but ADR-097 confirms built, extracted to own repo, published 0.3.1 to crates.io/npm.
+4. **ADR-152** — `Proposed` but CLAUDE.md + recent commits report §2.1–2.3/2.6 implemented, WiFlow-STD MEASURED-EQUIVALENT ~96% PCK.
+5. **ADR-154/155/156/157** (beyond-SOTA sweeps) — `Proposed` but each describes fixes **already landed with revert-verified regression tests**.
+6. **ADR-024 (AETHER) / 027 (MERIDIAN) / 072 (WiFlow)** — `Proposed` but CLAUDE.md lists them Accepted and code references them as implemented.
+7. **ADR-017** — header Accepted but CLAUDE.md still calls it "Proposed" (inverse drift).
+8. **ADR-018** — `Proposed` but ADR-012 cites it as the working firmware/aggregator impl.
+
+#### SEVERITY: HIGH — Status ahead of its dependencies (Accepted depends on Proposed)
+
+- **ADR-032** Accepted → depends on Proposed 029/030/031.
+- **ADR-053** Accepted → depends on Proposed ADR-052.
+- **ADR-048** Accepted → depends on Proposed ADR-045.
+- **ADR-077** Accepted → depends on Proposed ADR-075/076.
+
+#### SEVERITY: MEDIUM — Proposed-but-looks-abandoned (decisions that will likely never land)
+
+Cluster heads where the whole chain is Proposed with zero implementation evidence:
+- **ADR-003/007/008/009/010** — RuVector child ADRs orphaned after parent ADR-002 was superseded by 016/017.
+- **ADR-105/106/107/108** — entire federation chain, none implemented.
+- **ADR-118/119/120/121/122/123** — entire BFLD chain, all ACs unchecked, tracking issues TBD.
+- **ADR-124/125/126/127/128/129/130/133** — HOMECORE/bridge chain, multi-quarter future-dated, all TBD.
+- **ADR-033** (remote-viewing), **ADR-042** (CHCI, superseded-in-intent by 153), **ADR-046** (Android TV), **ADR-049** (Python v1 legacy), **ADR-067** (RuVector v2.0.5 upgrade not adopted), **ADR-074** (SNN), **ADR-085** (RaBitQ expansion), **ADR-011** (Proposed-URGENT despite proof pipeline live).
+
+#### SEVERITY: MEDIUM — Accepted but no implementation evidence (unverified "done")
+
+- **ADR-034** (FieldView mobile app) — Accepted, no crate/dir in CLAUDE.md.
+- **ADR-044** (wifi-densepose-geo) — bare Accepted, no Date/Deciders, crate not in CLAUDE.md table.
+
+#### Ranked actionable backlog (do in this order)
+
+1. **Resolve 6 duplicate ADR numbers + 3 missing-header files** (CRITICAL — breaks the index/tooling). Renumber 147×2, 148, 149, 050; demote 052-ddd appendix; resolve the 134 identity split; add Status headers to 147-proof, 134, 052-ddd.
+2. **Bulk-flip the 10 streaming-engine headers (ADR-136–145)** from Proposed → "Accepted — partial" — they have commit-pinned, test-backed Implementation Status notes. Highest ROI: one batch fixes the largest stale-status cluster.
+3. **Fix the status-graph inversions** (032/053/048/077 depend on Proposed parents; promote parents 029/030/031/045/052/075/076 to match their built reality, or downgrade the dependents).
+4. **Reconcile CLAUDE.md vs ADR headers** for 017, 024, 027, 072, 152 (doc says one thing, header another).
+5. **Triage the abandoned chains** (003/007–010, 105–108, 118–123, HOMECORE 124–133) — either mark `Rejected`/`Deferred` or open tracking issues; leaving ~50 Proposed-forever ADRs pollutes every gap analysis.
+6. **Verify or downgrade unsubstantiated Accepteds** (034, 044).
+
+**Bottom line:** the corpus's #1 defect is not abandoned work — it's **bookkeeping drift**. ~24 ADRs are mislabeled Proposed while code+tests exist, 6 numbers collide, and 3 files lack Status headers entirely. The status field cannot currently be trusted as a source of truth for what is built.
+
+---
+
+## Lens 2: supersession-chains
+
+I have all evidence needed. ADR-016 doesn't mention ADR-002 at all (only 014/015); ADR-017 discusses ADR-002 as a "correction" but never uses the word "supersede." This confirms the broken reciprocity. Final analysis below.
+
+### Supersession & Lifecycle Integrity — ADR Corpus
+
+Total declared supersession edges in census: **3** (ADR-002→016, ADR-002→017, ADR-052-tauri→054). All three were file-verified. Findings below; severity graded **CRITICAL / HIGH / MEDIUM / LOW**.
+
+#### Reconstructed chains
+- **ADR-002** (RuVector RVF Integration Strategy) → superseded-by **ADR-016 + ADR-017** (dual realization). Self-declared `supersedes` on 016/017.
+- **ADR-052-tauri** (Tauri Desktop Frontend) → superseded-by **ADR-054** (declared in 052's `superseded_by`).
+- No other formal `supersedes`/`superseded_by` links exist. No cycles detected (the only multi-node graph, ADR-002→{016,017}, is a DAG; ADR-052→054 is a single edge). **No cycles — clean.**
+
+#### Broken / asymmetric links
+
+**1. ADR-002 → ADR-016 / ADR-017: one-directional, never reciprocated. (HIGH)**
+ADR-002 header declares "Superseded by [ADR-016] and [ADR-017]" (`docs/adr/ADR-002-ruvector-rvf-integration-strategy.md:4`). But neither successor claims it:
+- **ADR-016** (`ADR-016-ruvector-integration.md`) never mentions ADR-002 anywhere — its `## References` lists only ADR-014/015. It does not assert supersession; the census `supersedes:["ADR-002"]` for ADR-016 is **unsupported by the file**.
+- **ADR-017** (`ADR-017-ruvector-signal-mat-integration.md`) discusses ADR-002 only as a `## Correction to ADR-002 Dependency Strategy` (line 532) — corrects "fictional crate names" — but **never uses the word "supersede."** Census `supersedes:["ADR-002"]` is again file-unsupported.
+- Net: ADR-002 points up at two ADRs that don't point back. The supersession is asserted by the superseded ADR alone — backwards from convention, and unverifiable from the successors.
+
+**2. ADR-002 partial-supersession leaves 5 orphaned children stranded. (HIGH)**
+ADR-002 is an umbrella whose children ADR-003, 007, 008, 009, 010 are still `Proposed`. ADR-016/017 only realize the *training/signal/MAT* integration points (mincut, attention, solver, etc.). The RVF-container (003), PQ-crypto (007), Raft consensus (008), WASM edge runtime (009), and witness-chains (010) decisions are **neither implemented nor formally superseded** — ADR-017:555 explicitly acknowledges 008/009 "described in ADR-002" are not carried forward. Marking the parent fully "Superseded" silently buries 5 live-but-abandoned child decisions. ADR-010's role is additionally filled de facto by ADR-028's witness-bundle without any supersession link.
+
+**3. ADR-052-tauri → ADR-054: declared by predecessor, not acknowledged by successor. (HIGH)**
+Census records ADR-052-tauri `superseded_by:["ADR-054"]`. **ADR-054 (`ADR-054-desktop-full-implementation.md`) contains zero references to ADR-052** (grep for `ADR-052|replac|supersed` returns nothing). ADR-054 is titled "RuView Desktop **Full Implementation**" and is "in progress" — functionally it's the implementation plan *for* 052, not a replacement. The supersession edge is unconfirmed by the successor and arguably mis-modeled (an in-progress impl doesn't supersede its own design ADR).
+
+#### Orphaned superseded ADRs still marked accepted/active
+**4. No classic orphan (superseded ADR still `Accepted`), but two soft variants: (MEDIUM)**
+- **ADR-052-tauri** is `Proposed` *and* `superseded_by ADR-054`, yet downstream ADR-053/055/056 (all `Accepted`) build on it and treat the desktop app as shipped (v0.3.0). A Proposed-and-superseded ADR anchoring three Accepted descendants is a lifecycle inconsistency: the live decision-of-record is ambiguous (052? 054? 056?).
+- **ADR-002** is correctly `Superseded`, so not an orphan — but ADR-038's roadmap census still counts it among 37 active ADRs, so stale references persist downstream.
+
+#### De-facto supersessions never recorded (missing links) — MEDIUM
+These pairs behave as supersession in the corpus but carry **no** `supersedes`/`superseded_by` fields, so the chain graph understates reality:
+- **ADR-098 ⇄ ADR-099** (`MEDIUM`): ADR-098 **Rejected** midstream; ADR-099 revives its carve-outs ("Adopt midstream…"). A rejection partially reversed by a later Proposed ADR — neither links the other via supersession fields (only prose tension).
+- **ADR-063 → ADR-064**, **ADR-035 → ADR-023/036**, **ADR-042 → ADR-153**, **ADR-050-provisioning → ADR-060**, **ADR-117 retracts PyPI v1.1.0**, PQ chain **ADR-100 → ADR-109 / ADR-107→108**: each is "superseded in scope/intent" per flags but has empty supersession fields. Not broken links (none falsely asserted), but **missing** ones — the lifecycle graph is incomplete.
+
+#### Cycles
+**None.** ADR-002→{016,017} and ADR-052→054 are acyclic; no ADR is reachable from its own successor.
+
+#### Severity summary
+| # | Issue | Severity |
+|---|-------|----------|
+| 1 | ADR-002 supersession not reciprocated by ADR-016/017 (016 never mentions 002; 017 only "corrects") | HIGH |
+| 2 | ADR-002 children 003/007/008/009/010 stranded under a "fully superseded" parent | HIGH |
+| 3 | ADR-052→054 edge unacknowledged by ADR-054 (no reference); likely mis-modeled (impl, not replacement) | HIGH |
+| 4 | ADR-052-tauri Proposed+superseded yet anchors Accepted 053/055/056 | MEDIUM |
+| 5 | De-facto supersessions (098/099, 063/064, 042/153, 050/060, 035/023, 100/109) unrecorded | MEDIUM |
+| — | Cycles | none (clean) |
+
+Highest-priority fix: add reciprocal `supersedes: ADR-002` language to ADR-016/017 (or downgrade the claim), and split ADR-002's status to "partially superseded" so children 003/007/008/009/010 aren't silently closed.
+
+---
+
+## Lens 3: contradictions
+
+All findings confirmed against source. Here is the contradictions lens.
+
+### Contradictions & Retractions Lens — ADR Corpus
+
+The sweep (ADR-154–163) is itself a structured retraction layer: each "Beyond-SOTA / anti-AI-slop" ADR exists *because* an earlier accepted claim was found false. Findings graded **CRITICAL** (life-safety, security, or a published accuracy number that was meaningless) / **HIGH** (a capability/number retracted or directly contradicted) / **MEDIUM** (status or scope conflict) / **LOW** (cosmetic/doc drift).
+
+#### A. Accepted/published claims later RETRACTED or REFUTED
+
+**[CRITICAL] ADR-155 retracts every prior NN accuracy/TTA/proof claim.** ADR-155 §2.2 discloses `bin/train.rs` validated a *real* MM-Fi training run against a **synthetic** val set, and windows leak at stride-1 (~99% overlap) — *"any PCK it printed was meaningless on two counts."* §2.3: `rapid_adapt.rs` `contrastive_step`/`entropy_step` wrote a **fake gradient** (`grad += v * 0.01`) unrelated to the objective — every "TTA improves the metric" result was unsupported. §2.4: the deterministic proof **self-certified** (`generate_expected_hash` blessed whatever the pipeline emitted; PASS counted any loss decrease incl. 1e-9 float noise; missing hash defaulted to PASS). This retroactively voids accuracy claims made anywhere in the corpus that depended on the training/proof path prior to commit landing ADR-155.
+
+**[CRITICAL] ADR-154 retracts the ADR-134 CIR coherence gate as live.** ADR-152/CLAUDE.md present CIR (ADR-134) as a contributing signal in the multistatic coherence gate. ADR-154 §2 proves it was **DEAD in production for every canonical frame**: the HT20 CIR estimator returns `SubcarrierMismatch` on all 56-tone canonical frames (`cir_gate_ht20_is_dead_on_canonical56`: 0 Ok / 8 mismatch), so `coherence = 0.7·freq + 0.3·dominant_tap_ratio` silently degraded to freq-only (`cir_gate_dead_ht20_equals_gate_off`, |Δ|<1e-9). Any ADR claiming CIR-enhanced coherence/ToF before this fix overstated reality.
+
+**[CRITICAL] ADR-079 internal accuracy contradiction (self-flagged in census, confirmed).** Context states proxy PCK@20 = **2.5%** (lines 11, 25) and "10-20x improvement: 2.5% → 35%+". The baseline table (line 497) reports proxy PCK@20 = **35.3%** — i.e. the *baseline already equals the stated target* — while per-joint upper body (nose/shoulders/wrists) is **0%** (line 503). The headline 10–20x improvement number is therefore self-refuting against its own baseline table. CLAUDE.local.md adds the local-Windows attempt (#640) measured **0% PCK**. An Accepted ADR with three mutually inconsistent values for its own central metric.
+
+**[HIGH] ADR-152 self-refutes one verified research claim (F4).** ADR-152 grades 25 claims 3-vote; §F4 records the "Espressif `esp_wifi_sensing` is **drop-in compatible with RuView nodes**" claim **REFUTED 0-3** (WiFi-6 parts use a different CSI acquisition config struct). ADR-110 ("ESP32-C6 Wi-Fi 6 CSI") and the CLAUDE.md hardware table treat C6/Wi-Fi-6 CSI as a smooth extension; ADR-152 also notes HE-CSI needs ESP-IDF ≥5.5 (v5.4 silently downconverts to HT). The "WiFlow-STD MEASURED-EQUIVALENT ~96% PCK@20" line in CLAUDE.md is *not* yet supported: §2.2/§F1 mark external pose numbers (incl. the 97.25% WiFlow-STD figure) **CLAIMED**, and §F1 explicitly forbids citing 97.25% as comparable until measurements (a)–(c) are run. CLAUDE.md asserting "MEASURED-EQUIVALENT" contradicts the ADR's own gating.
+
+**[HIGH] ADR-150 retracts the implied cross-subject capability of the encoder line.** AETHER/MERIDIAN ADRs (024/027) and the foundation-encoder framing imply subject-invariant embeddings work. ADR-150 measures **81.63% in-domain vs ~11.6% leakage-free cross-subject** torso-PCK, and reports DANN **failed** (27.26%→27.54%, empirically ~0 gain) and bigger capacity *hurt* (transformer 24.8% < conv 27.3%). §1.1/§4 conclude the cross-subject acceptance gate "is **unlikely to be met without new multi-subject** data" — a direct retraction of the "more capacity / adversarial alignment solves cross-environment loss" premise underlying ADR-027.
+
+**[HIGH] ADR-159 refutes the "never identified anyone" accusation but simultaneously retracts cog-person-count's marketing.** ADR-159 ships real SHA-pinned Candle models, but discloses person-count `training_class1_accuracy = 0.343` (presence-only, classes 0/1), and **renames** the Cargo description from "learned multi-person counter" → "presence detector + (data-gated) person count," clamping/`low_confidence`-flagging multi-occupant counts. This retracts ADR-103's "learned multi-person counter (SOTA WiFi CSI counting)" claim and ADR-104's count tool, which depended on it.
+
+**[HIGH] ADR-161 retracts HOMECORE server security + functionality claims.** ADR-130 (HOMECORE-API, wire-compatible, Ed25519-JWT) implied a secured server. ADR-161 fixes a **CRITICAL WebSocket auth bypass** (any non-empty token accepted), "reply-theater" (WS responses computed then discarded), and documented-but-no-op automation — then ADR-162 enforces the ADR-161 deferrals (plugin Ed25519 sig verification, capability isolation, bounded RunModes that were "parsed-but-unenforced/unbounded-parallel"), retracting ADR-128/129's implied plugin-signing and automation guarantees.
+
+**[MEDIUM] ADR-163 converts CLAIMED latency budgets to MEASURED — retracting prior budget citations.** ADR-160/159 cited wasm-edge/cog latency *budgets*. ADR-163 adds host benches and explicitly states the **ESP32/Xtensa-on-hardware figure remains UNMEASURED** — so any doc citing the device latency budget as achieved is unsupported.
+
+**[MEDIUM] ADR-098 → ADR-099 partial reversal.** ADR-098 **Rejected** midstream as a system component; ADR-099 (Proposed) **adopts** midstream's temporal-compare (DTW) + temporal-attractor-studio as a parallel tap. Framed as "complementary," but it revives the exact carve-outs ADR-098 declined to integrate — a live decision conflict pending resolution.
+
+**[MEDIUM] ADR-147 (OccWorld) self-retracts Cosmos.** The accepted ADR-147 title/decision was revised from "NVIDIA Cosmos WFM Integration" to OccWorld after a hardware finding (Cosmos needs 32.5 GB VRAM); Cosmos is retracted as primary. The companion ADR-147-benchmark-proof reports 213 ms/inference on **random weights, no checkpoint** — a baseline-without-fine-tuning number that must not be cited as a quality/target metric.
+
+#### B. Pairs making CONFLICTING decisions on the same topic
+
+**[HIGH] RVF-WASM edge runtime — ADR-009 vs shipped `wifi-densepose-wasm`.** ADR-009 (Proposed) decides to **replace** the existing wifi-densepose-wasm approach with an `.rvf.edge` container runtime. The crate it proposes to replace is shipped and in the CLAUDE.md crate table (and is the dependency base for ADR-058/059 browser pose). ADR-009 is an unrealized decision directly contradicting shipped architecture.
+
+**[HIGH] Witness/audit mechanism — ADR-010 vs ADR-028.** ADR-010 (Proposed) decides RuVector witness *chains* as "the primary tamper-evident audit mechanism." ADR-028 (Accepted, implemented) established a different **witness-bundle** mechanism (verify.py / SHA-256 / VERIFY.sh) that fills this role. Two competing "primary audit" decisions; ADR-010 is stranded.
+
+**[HIGH] Multistatic "sensing-first RF mode" — ADR-029 vs ADR-031 near-duplicate scope.** Both decide a "sensing-first RF mode for multistatic fidelity": ADR-029 (RuvSense, signal/src/ruvsense/) and ADR-031 (RuView cross-viewpoint fusion, ruvector/src/viewpoint/). Overlapping problem statements (occlusion/depth/multi-person via multistatic attention+geometry), separate crate homes, both still nominally "Proposed" while both are implemented. Unreconciled dual ownership of the multistatic-fusion decision.
+
+**[MEDIUM] Person-counting decision conflict — ADR-037 vs ADR-075 vs ADR-103.** Three different decisions to replace the same fixed-threshold counter: ADR-037 (4-phase neural decomposition), ADR-075 (spectral min-cut over subcarrier-correlation graph, fixes #348), ADR-103 (learned Cog `cog-person-count`). ADR-075's bug (#348) overlaps ADR-069's driver. None supersedes the others; ADR-159 then guts ADR-103's claim (above).
+
+**[MEDIUM] PQ-crypto signing — ADR-007 vs ADR-109.** ADR-007 (Proposed) decides Ed25519 + ML-DSA-65 hybrid for sensing-data signing; ADR-109 (Proposed) decides Ed25519 + **Dilithium-3** hybrid for cog signing (Dilithium = ML-DSA family but a different parameter pick/scope). Two PQ-signature decisions over adjacent surfaces with non-identical algorithm choices, neither reconciled.
+
+**[MEDIUM] Federation key-exchange self-supersession — ADR-107 vs ADR-108.** ADR-107 adopts classical Diffie-Hellman in secure-aggregation Layer 4; ADR-108 replaces it with Kyber-768 because the DH choice is "quantum-vulnerable." ADR-108 supersedes a core element of ADR-107 while ADR-107 is still only Proposed — a decision corrected before it was ever accepted.
+
+**[MEDIUM] Provisioning path forked three ways — ADR-050(prov) vs ADR-060 vs ADR-052/054.** ADR-050 (provisioning-tool-enhancements, Proposed) scopes channel+MAC-filter flags; ADR-060 (Accepted) actually implements them; ADR-052/054 move provisioning into a Rust-native Tauri desktop path. Three live decisions for "how RuView provisions nodes," with ADR-060 partially fulfilling ADR-050 without superseding it.
+
+#### C. Status-graph contradictions (Accepted depending on / contradicting Proposed)
+
+**[MEDIUM] Accepted ADRs hardening/depending on Proposed ones.** ADR-032 (Accepted, security hardening) hardens ADR-029/030/031 which remain "Proposed" — an accepted decision presupposing un-accepted ones exist. Same pattern: ADR-048 (Accepted) depends on ADR-045 (Proposed); ADR-053 (Accepted) depends on ADR-052 (Proposed); ADR-077 (Accepted) depends on ADR-075/076 (Proposed); ADR-104 (Accepted) depends on ADR-103 (Proposed). These are status contradictions, not capability retractions, but they signal the same "header lags reality" hygiene problem the sweep is correcting.
+
+**[LOW] Header-stale-vs-implementation (pervasive).** ADR-029/030/031, 072, 095/096, 136–145, 150, 152, 154–157 all carry `Status: Proposed` while their own appended Implementation-Status notes (or downstream ADRs / CLAUDE.md) report them built+tested with commits. ADR-024/027 say Proposed; CLAUDE.md lists them Accepted; pose_tracker.rs already uses AETHER re-ID. Cosmetic but corpus-wide; it is the mechanism by which retracted/overstated claims survive (a green "built" note under a "Proposed" header is exactly where ADR-155's self-certifying proof hid).
+
+#### Cited source files (absolute)
+- C:\Users\ruv\Projects\wifi-densepose\docs\adr\ADR-079-camera-ground-truth-training.md (lines 11/25/497/503 — 2.5% vs 35.3% vs 0%)
+- C:\Users\ruv\Projects\wifi-densepose\docs\adr\ADR-150-rf-foundation-encoder.md (81.63% vs 11.6%; DANN ~0)
+- C:\Users\ruv\Projects\wifi-densepose\docs\adr\ADR-152-wifi-pose-sota-2026-intake.md (F4 REFUTED 0-3; 97.25% CLAIMED-not-MEASURED)
+- C:\Users\ruv\Projects\wifi-densepose\docs\adr\ADR-154-signal-dsp-beyond-sota.md (§2 dead CIR gate)
+- C:\Users\ruv\Projects\wifi-densepose\docs\adr\ADR-155-nn-training-beyond-sota.md (§2.2–2.4 synthetic-val / fake gradient / self-certifying proof)
+- C:\Users\ruv\Projects\wifi-densepose\docs\adr\ADR-159-cognitum-appliance-beyond-sota.md (person-count 0.343; description renamed)
+
+**Top-severity summary:** the four CRITICAL items (ADR-155 fake-gradient+synthetic-val+self-certifying proof; ADR-154 dead CIR gate; ADR-079 self-inconsistent PCK; ADR-161 WS auth bypass) are the corpus's load-bearing "AI-slop" admissions — each is an *accepted-or-shipped* surface whose stated accuracy/security/function was provably false until the sweep landed. Every accuracy number predating ADR-155 in any other ADR should be treated as CLAIMED, not MEASURED, until re-derived through the post-155 leak-free split.
+
+---
+
+## Lens 4: coverage-gaps
+
+Confirmed — ADR-094 governs the pointcloud *viewer deployment* (proposed-only), not the crate's sensing-data-production contract. I have all evidence needed.
+
+### Coverage Gaps — Crates/Capabilities vs Governing ADRs
+
+Severity: **CRITICAL** (shipped code with no/broken governing ADR), **HIGH** (architect would expect an ADR, none exists), **MEDIUM** (governed only by a remediation/deploy ADR, no creation/architecture ADR), **LOW** (minor).
+
+#### A. Shipped crates whose cited ADR does not exist (CRITICAL)
+
+Two crates are built and in-tree but reference ADR numbers that point to *different* on-disk ADRs or to files that never existed (confirmed: no `ADR-131*.md` or `ADR-132*.md` exists; `ADR-134` on disk is CIR, not HOMECORE-MIGRATE):
+
+- **`v2/crates/homecore-recorder`** — Cargo.toml header: *"SQLite state history + semantic search (ADR-132)"*. **No ADR-132 exists.** The HOMECORE series map (ADR-126 §4) lists ADR-132 HOMECORE-RECORDER as planned, but it was never written. A shipped persistence/history crate has zero governing decision record. **CRITICAL** — this is the recorder, the durable-state surface, ungoverned.
+- **`v2/crates/homecore-migrate`** — Cargo.toml header: *"Implements ADR-134 (HOMECORE-MIGRATE)"*. **On-disk ADR-134 is "First-Class CIR Support"** (census + glob confirm). ADR-129/126 also cite ADR-134 as HOMECORE-MIGRATE. The crate implements a migration tool from Python HA reading `.storage/*.json` — a data-integrity-sensitive importer — governed by a phantom ADR identity. **CRITICAL** (compounds the documented ADR-134 duplicate-number collision).
+
+These are not stale-header issues like the ADR-136..146 cluster (where the ADR exists and is just marked Proposed); here the cited governing ADR **is absent or is a different decision**.
+
+#### B. Shipped crates with NO governing ADR at all (HIGH)
+
+- **`v2/crates/wifi-densepose-engine`** — *"streaming-engine integration layer — composes the ADR-135..146 building blocks into one trust-traceable pipeline cycle."* It composes ~12 ADRs' outputs into the live pipeline-cycle aggregate, but **no ADR governs the composition/orchestration contract itself** (ordering, back-pressure, the "one pipeline cycle" boundary). ADR-136 defines frame contracts/stages but not the integrator crate. An architect would expect an ADR for the seam that wires 135–146 onto the live 20 Hz path — exactly the "integration glue not yet on live path" caveat repeated across ADR-136..146. **HIGH.**
+
+#### C. Capabilities governed only by a remediation/deploy ADR — no creation/architecture ADR (MEDIUM)
+
+- **`v2/crates/wifi-densepose-wasm-edge` (~70 edge skills)** — The only ADRs touching it are **ADR-160** (honest *relabeling*/soundness cleanup) and **ADR-163** (latency *measurement*). Both are anti-slop remediation ADRs that presuppose ~70 skills already shipped. There is **no creation/architecture ADR** defining the skill taxonomy, ABI, event-ID allocation, or budget tiers for this crate. (Contrast ADR-041, which *does* catalog the 60-module registry — but for the ESP32/WASM3 on-device path of ADR-040, a different artifact.) A whole ~70-module crate's design rationale lives nowhere. **MEDIUM-HIGH.**
+- **`v2/crates/wifi-densepose-occworld-candle`** — *"OccWorld TransVQVAE inference ported to Candle (Rust-native, no Python IPC)."* ADR-147 (OccWorld) decided a **Python-subprocess** thin client and explicitly deferred a Rust backend swap to "Phase B / RoboOccWorld." A native Candle reimplementation is a material architecture change (new dep surface, no IPC, weight-loading path) that **no ADR records the decision to build now**. **MEDIUM.**
+- **`v2/crates/wifi-densepose-pointcloud`** — ADR-094 governs only the *GitHub-Pages viewer deployment* (Proposed). The crate as a **point-cloud data-production/format contract** (what it emits, schema, real-data-stream toggle wiring) has no governing decision beyond the demo-deploy doc. **MEDIUM.**
+- **`v2/crates/homecore-hap`** — header cites ADR-125 P1 scaffold; ADR-125 (Apple Home HAP bridge) exists and covers it. **Governed — no gap.** (Listed to scope out the false positive.)
+- **`v2/crates/wifi-densepose-geo`** — governed by ADR-044 (geospatial). Governed, but ADR-044 is a bare "Accepted" with no implementation evidence and is cross-referenced incorrectly by ADR-052 (cites ADR-044 for provisioning). **LOW** (governed but the ADR itself is thin).
+
+#### D. Decision areas an architect would expect an ADR for, but none exists (HIGH)
+
+1. **Persistence/storage strategy for HOMECORE state history** — `homecore-recorder` ships SQLite with an "HA-compat schema," but no ADR decides SQLite-vs-alternatives, retention, or the semantic-search index. Recorder is the durability backbone; an unrecorded storage choice is a classic missing-ADR. **HIGH** (ties to gap A).
+2. **Python-HA → HOMECORE migration/import contract** — `homecore-migrate` reads foreign `.storage` JSON (untrusted input, schema-drift risk) with no governing ADR (the cited one is CIR). Migration correctness and trust boundary are exactly what an ADR should pin. **HIGH** (ties to gap A).
+3. **The streaming-engine *integrator* contract** (`wifi-densepose-engine`) — see B. **HIGH.**
+4. **Cross-crate workspace dependency/publishing ADR** — CLAUDE.md lists a hand-maintained 12-step publishing order and a 15-crate table, but the workspace now has **38 crates** (glob count) including ungoverned ones (engine, worldmodel, worldgraph, occworld-candle, geo, wasm-edge, homecore-*, cog-*, ruview-swarm, pointcloud, nvsim-server, desktop). No ADR governs crate-graph topology / publish boundaries at this scale — the publishing list in CLAUDE.md is already stale against reality. **MEDIUM-HIGH.**
+5. **No ADR ties the streaming-engine (`engine`) to the cog/appliance deploy surface** — ADR-101/102/159 govern cogs; ADR-136..146 govern the engine; nothing decides how the trust-traceable engine output becomes a deployed cog. The seam between the two largest subsystems is ungoverned. **MEDIUM.**
+
+#### E. Scoped-out false positives (verified governed)
+
+- `wifi-densepose-worldmodel` → ADR-147 (OccWorld bridge). Governed.
+- `wifi-densepose-worldgraph` → ADR-139. Governed.
+- `cog-ha-matter` → ADR-116; `cog-person-count` → ADR-103; `cog-pose-estimation` → ADR-101. Governed.
+- `ruview-swarm` → ADR-148. `nvsim`/`nvsim-server` → ADR-089/092. `wifi-densepose-bfld` → ADR-118–123/141. `wifi-densepose-calibration` → ADR-151. All governed.
+- `wifi-densepose-desktop` → ADR-052/054 (contested status, but an ADR exists). Not a coverage gap (it's a status-drift issue, out of this lens's scope).
+
+#### Top-priority remediation (concrete)
+1. Write **ADR-132 HOMECORE-RECORDER** (or renumber) so the shipped `homecore-recorder` SQLite/history crate has a real governing decision — **CRITICAL**.
+2. Resolve the **ADR-134 identity collision** and create a real **HOMECORE-MIGRATE** ADR for `homecore-migrate` (untrusted-import trust boundary) — **CRITICAL**.
+3. Write a **streaming-engine integrator ADR** for `wifi-densepose-engine` (the 135–146 composition contract / live-path seam) — **HIGH**.
+4. Write a **creation/architecture ADR for `wifi-densepose-wasm-edge`** (taxonomy/ABI/event-IDs) — currently only remediation ADRs (160/163) exist — **MEDIUM-HIGH**.
+5. Add an ADR for the **`occworld-candle` Rust-native backend swap** (ADR-147 only blessed the Python-subprocess path) — **MEDIUM**.
+
+Evidence files: `v2/crates/homecore-recorder/Cargo.toml`, `v2/crates/homecore-migrate/Cargo.toml`, `v2/crates/wifi-densepose-engine/Cargo.toml`, `v2/crates/wifi-densepose-occworld-candle/Cargo.toml`, `docs/adr/ADR-134-csi-to-cir-time-domain-multipath.md` (CIR, not MIGRATE), `docs/adr/ADR-160-edge-skill-library-honest-labeling.md`, `docs/adr/ADR-094-pointcloud-github-pages-deployment.md`; absence confirmed via glob: no `ADR-131*`, no `ADR-132*`.
+
+---
+
+## Lens 5: data-hardware-gated
+
+Evidence confirmed. I have enough to write the section.
+
+### Open / Gated Decisions — The Real Backlog (data/hardware-gated, in-progress, or unresolved)
+
+Severity = how load-bearing the unresolved decision is to a shipped claim. Sweep coverage = whether ADR-154–163 touched it.
+
+#### CRITICAL — life-safety or shipped-claim surface, still gated
+
+**ADR-079 — Camera Ground-Truth Training Pipeline.** *Accepted, but core decision unvalidated.* P7–P9 (real paired-data collection, training, cross-room LoRA) are **Pending** (file lines 476–478). Blocker: a real synchronized camera+ESP32 paired-capture session and GPU training run — neither done. The ADR's own baseline table is self-contradictory: text says proxy PCK@20=2.5% (lines 11, 25) yet line 497 reports 35.3% (the *target*) with line 503 confessing **upper-body joints at 0%** — the proxy has no real spatial signal. CLAUDE.local.md records the local-Windows attempt (#640) at 0% PCK. The fleet (ruvultra RTX 5080, cognitum-seed-1) is the unblock, but the decision is accepted-on-paper, not proven. **Sweep: NOT addressed** — 154–163 never touch the camera-teacher path. Real open backlog item.
+
+**ADR-158 — MAT/World-Model sweep (life-safety).** *Accepted/implemented for the correctness fixes, but capability remains DATA-GATED.* The sweep honestly fixed the dangerous bugs (unified the two divergent triage engines so survivor count can't inflate from repeat detection — lines 46–56, 184–186), but explicitly grades the actual capabilities as unproven: **RF-through-rubble survivor detection = DATA-GATED** (needs instrumented rubble trials, line 37); **learned multi-person counter = DATA-GATED** on labelled multi-occupant CSI (lines 41, 173); PicoScenes/Intel-5300/Atheros live capture DATA-GATED on NIC/driver hardware (lines 177–179). **Sweep: addressed the slop, honestly deferred the capability.** This is the model the rest should follow — code is real, accuracy claim is withheld pending absent hardware. Severity CRITICAL because it is the life-safety surface; the residual gate is acceptable and labeled.
+
+#### HIGH — shipped/benchmarked claim with an explicit residual gate
+
+**ADR-152 — WiFi-Pose SOTA 2026 Intake.** Status header stale (says Proposed; commits + line 58 report §2.1–2.3/2.6 implemented and WiFlow-STD **MEASURED-EQUIVALENT 96.09% PCK@20** on RTX 5080). Residual gates are real and disclosed: (1) **1 of 25 verified claims REFUTED 0-3** — "ESP WiFi-6 drop-in compatible with RuView nodes" is false (WiFi-6 parts use a different CSI acquisition struct, lines 31, 123); (2) external pose numbers (PerceptAlign −60% cross-domain; UNSW MAE pose transfer) remain **CLAIMED until reproduced on our hardware** (lines 21, 27, 119–122); (3) measurement (b)/(c) open — line 111 confirms pretrained init gives optimization transfer but **no feature transfer**, and no run beat a mean-pose baseline on single-subject data, so **no CSI→pose capability is citable** until multi-subject/multi-position data exists. Blocker: heterogeneous multi-subject CSI dataset (data-gated, per ADR-150 §F3). **Sweep: this ADR *is* the prove-everything discipline applied to research intake** — gates labeled, not buried.
+
+**ADR-072 / ADR-150 — WiFlow pose + RF foundation encoder.** ADR-072 >80% PCK@20 target unverifiable without camera labels (resolved-path via ADR-079, itself gated above). ADR-150 cites measured 81.63% in-domain vs **~11.6% leakage-free cross-subject** — the cross-subject collapse is real and the stated lever (ADR-152 F3) is *more heterogeneous data*, not capacity. Blocker: multi-subject/room dataset + libtorch GPU training. **Sweep: NOT directly addressed** (155 fixed PCK/OKS metric-integrity plumbing, which makes these numbers *trustworthy* but doesn't close the data gap).
+
+#### HIGH — security/privacy decisions still Proposed-only (no sweep touched the gate itself)
+
+**ADR-080 — QE Remediation.** Tracks unfixed security HIGH findings (X-Forwarded-For bypass, leaked stack traces, JWT-in-URL CWE-598), gate FAILED, status Proposed, no done-marking. The HOMECORE sweep (ADR-161/162) fixed *HOMECORE*'s WS-auth bypass and plugin signing — a **different** server boundary. **Sweep: did NOT cover ADR-080's sensing-server findings.** Genuine open security backlog.
+
+**ADR-105→109, ADR-118–125 (BFLD/federation/fabric chains).** Entire federation chain (105–109) and BFLD surface (118–125) are Proposed-only, all ACs unchecked, several "tracking issue TBD." Blockers: KIT BFId dataset (ADR-121 calibration), Pi5/Nexmon CBFR capture hardware (ADR-123 — ESP32 *structurally cannot* sniff CBFR), Soul-Signature + cog-ha-matter dependencies (ADR-122/125). **Sweep: NOT addressed** — 154–163 stop at HOMECORE/MAT/cog/edge; the privacy control *plane* (ADR-141, built) exists but the BFLD *capture/scoring* chain it would gate does not. Backlog, honestly gated by absent hardware.
+
+#### MEDIUM — hardware-gated, honestly deferred BY the sweep (lowest risk)
+
+**ADR-163 — Edge-latency measurement.** *Accepted/implemented* for host benches, but the **ESP32/Xtensa on-hardware `process_frame` figure is explicitly UNMEASURED / PENDING (hardware)** (lines 31–32, 79–83, 92–93). Blocker: `wasm32-unknown-unknown` built + flashed to ESP32-S3 and timed on-device; host x86_64 median is "an upper bound on algorithm work, not the ESP32 number." This is the **gold-standard deferral**: the gate is stated everywhere, no claim overreaches. **Sweep: this *is* a sweep ADR honestly deferring its own residual.**
+
+**ADR-160 — wasm-edge skill labeling.** Medical/affect/weapon capabilities explicitly **NOT validated** — relabelled/disclaimed/feature-gated rather than implemented, reference-standard-gated. **Sweep: addressed by relabeling, capability honestly deferred.**
+
+**ADR-110 — ESP32-C6 firmware.** Implemented, but HE-CSI requires ESP-IDF ≥5.5 (v5.4 silently downconverts to HT) — capability hardware/toolchain-gated per WITNESS §B1. Not a sweep target; gate is a noted hardware constraint, not slop.
+
+**Other purely hardware/data-gated Proposed decisions (no sweep involvement, no overreach):** ADR-023 (paired data+GPU), ADR-027/MERIDIAN (multi-env data), ADR-042 CHCI (custom PCB/TCXO — largely superseded by 153), ADR-063/064 (ESP32-C6+MR60BHA2 mmWave), ADR-065/066 (live Cognitum Seed deploy), ADR-070 (live 2-node+Seed capture), ADR-073/078 (multi-AP mesh deployment), ADR-083 (pending field evidence), ADR-086 (real-deployment suppression rates), ADR-091 (COTS sub-THz + ITAR-clear use case), ADR-103 (labelled count data), ADR-113 (Fresnel-sim, not hardware-validated), ADR-114 (real NV-diamond device), ADR-134/135 (COM9/COM12 hardware-test feature), ADR-143 v2 (7-day fleet validation campaign, dead-code until then), ADR-144 (no UWB radio in fleet).
+
+#### Cross-cutting finding
+The sweep (ADR-154–163) is **narrowly scoped**: it hardened MAT (158), Cognitum cogs (159), wasm-edge (160), HOMECORE server+plugins (161/162), and latency debt (163) — converting CLAIMED→MEASURED or DATA-GATED with honest labels. It **did not** touch the two largest *capability* gaps: the **camera-teacher training validation (ADR-079/072/150)** and the **federation/BFLD privacy chains (105–109, 118–125)** — both remain data/hardware-gated and Proposed-only. The single hard contradiction worth flagging to a human: **ADR-079's baseline table reports the target (35.3%) as if achieved while the prose and #640 evidence say 2.5%/0%** — that is the one place a reader could mistake an aspiration for a measurement.
@@ -1,5 +1,6 @@
 # homecore-migrate — Migration tooling from Python Home Assistant.
-# Implements ADR-134 (HOMECORE-MIGRATE), P1 scaffold:
+# Implements ADR-165 (HOMECORE-MIGRATE), P1 scaffold:
+# (was cited as "ADR-134"; renumbered to ADR-165 — on-disk ADR-134 is CIR. See ADR-164/ADR-165.)
 #   - HaStorageDir + HaStorageEnvelope: reads `.storage/*.json` files
 #   - Versioned format parsers under `storage_format::v<N>`
 #   - entity_registry, device_registry, config_entries parsers
@@ -14,7 +15,7 @@ version = "0.1.0-alpha.0"
 edition = "2021"
 license = "MIT"
 authors = ["rUv <ruv@ruv.net>", "HOMECORE Contributors"]
-description = "Migration tooling from Python Home Assistant to HOMECORE (ADR-134 P1 scaffold)"
+description = "Migration tooling from Python Home Assistant to HOMECORE (ADR-165 P1 scaffold)"
 repository = "https://github.com/ruvnet/RuView"

 [[bin]]
@@ -6,7 +6,7 @@ Migration tooling for importing Home Assistant configuration, entities, and secr
 ![License](https://img.shields.io/badge/license-MIT-blue.svg)
 ![MSRV: 1.89+](https://img.shields.io/badge/MSRV-1.89%2B-purple.svg)
 [![Tests](https://img.shields.io/badge/tests-19%20passing-brightgreen.svg)](https://github.com/ruvnet/RuView)
-[![ADR-134](https://img.shields.io/badge/ADR-134-orange.svg)](../../docs/adr/ADR-134-homecore-migration-from-python-ha.md)
+[![ADR-165](https://img.shields.io/badge/ADR-165-orange.svg)](../../docs/adr/ADR-165-homecore-migrate-from-home-assistant.md)

 Parse and inspect Home Assistant's `.storage/` directory, entity registry, device registry, secrets, and automations. Convert existing HA configurations for import into HOMECORE (full conversion in P2).

@@ -22,7 +22,7 @@ Parse and inspect Home Assistant's `.storage/` directory, entity registry, devic
 - **Automations parser** — reads `automations.yaml` and counts/lists automations (full conversion in P2)
 - **CLI binary** — `homecore-migrate inspect` to preview what will be migrated

-The tool enforces version schema compatibility: unknown HA schema versions are rejected (hard error per ADR-134 §6 Q5) rather than silently corrupting data.
+The tool enforces version schema compatibility: unknown HA schema versions are rejected (hard error per ADR-165 §6 Q5) rather than silently corrupting data.

 ## Features

@@ -136,7 +136,7 @@ homecore-migrate (import from HA)

 ## References

- [ADR-134: HOMECORE Migration from Python Home Assistant](../../docs/adr/ADR-134-homecore-migration-from-python-ha.md)
+- [ADR-165: HOMECORE Migration from Python Home Assistant](../../docs/adr/ADR-165-homecore-migrate-from-home-assistant.md)
 - [ADR-126: HOMECORE Home Assistant Port (master)](../../docs/adr/ADR-126-homecore-home-assistant-port.md)
 - [Home Assistant .storage/ format](https://developers.home-assistant.io/docs/storage/)
 - [homecore-migrate CLI source](src/main.rs)
@@ -1,6 +1,6 @@
 //! Parser for `core.config_entries` (HA storage schema v1, minor_version varies).
 //!
-//! Per ADR-134 §6 Q5, `.storage/core.config_entries` format is undocumented
+//! Per ADR-165 §6 Q5, `.storage/core.config_entries` format is undocumented
 //! and version-gated. P1 reads the envelope and emits:
 //!   - count of config entries
 //!   - list of integration domains represented
@@ -1,7 +1,8 @@
 //! homecore-migrate — Migration tooling from Python Home Assistant.
 //!
-//! Implements [ADR-134](../../docs/adr/ADR-134-homecore-migration-from-python-ha.md)
-//! (referenced via ADR-126 §4, series map row ADR-134 HOMECORE-MIGRATE).
+//! Implements [ADR-165](../../docs/adr/ADR-165-homecore-migrate-from-home-assistant.md)
+//! (HOMECORE-MIGRATE; ADR-126 §4 series map labels the role "ADR-134 HOMECORE-MIGRATE",
+//! but on-disk ADR-134 is CIR — the migrate decision was renumbered to ADR-165. See ADR-164).
 //!
 //! ## P1 scope
 //!
@@ -56,7 +57,7 @@ pub enum MigrateError {

    /// Fired when the outer `{version, minor_version}` envelope version is
    /// known but the `minor_version` is not supported by any compiled parser.
-    /// Per ADR-134 §6 Q5: hard error on unknown minor_version.
+    /// Per ADR-165 §6 Q5: hard error on unknown minor_version.
    #[error(
        "unsupported schema version in {file}: \
         version={version} minor_version={minor_version}. \
@@ -5,7 +5,7 @@
 //! adding a new `v<N>.rs` module; the dispatch function in each parser module
 //! routes to the right implementation.
 //!
-//! Per ADR-134 §6 Q5: unknown `minor_version` values produce a hard
+//! Per ADR-165 §6 Q5: unknown `minor_version` values produce a hard
 //! `MigrateError::UnsupportedSchemaVersion` — we do NOT silently fall back
 //! to an older parser, because schema changes can be load-bearing (new fields,
 //! renamed keys, semantic reinterpretations).
@@ -682,8 +682,9 @@ mod tests {
    fn contradiction_demotes_privacy() {
        let (mut e, room) = engine();
        let cal = CalibrationId(7);
-        // 2 ms spread: within the 5 ms hard guard but above the 1 ms soft guard.
-        let frames = [node_frame(0, 1000, 56), node_frame(1, 3000, 56)];
+        // 25 ms spread: within the 60 ms hard guard but above the 20 ms soft
+        // guard (#1031 raised both to accommodate the real TDM slot offset).
+        let frames = [node_frame(0, 1_000, 56), node_frame(1, 26_000, 56)];
        let out = e.process_cycle(&frames, cal, room, 20_000).unwrap();

        assert!(out.demoted, "loose alignment must demote");
@@ -17,6 +17,7 @@ pub mod graph_transformer;
 pub mod host_validation;
 pub mod introspection;
 pub mod matter;
+pub mod model_format;
 pub mod mqtt;
 pub mod path_safety;
 pub mod semantic;
@@ -14,6 +14,7 @@ pub mod cli;
 pub mod csi;
 mod engine_bridge;
 mod field_bridge;
+mod model_format;
 mod multistatic_bridge;
 pub mod pose;
 mod rvf_container;
@@ -144,6 +145,16 @@ struct Args {
    #[arg(long, value_name = "PATH")]
    export_rvf: Option<PathBuf>,

+    /// Convert a published model file (model.safetensors / model.rvf.jsonl) to
+    /// the RVF binary container the --model loader expects, then exit (#894).
+    /// Pair with --convert-out for the destination path.
+    #[arg(long, value_name = "PATH")]
+    convert_model: Option<PathBuf>,
+
+    /// Output path for --convert-model (defaults to <input>.rvf).
+    #[arg(long, value_name = "PATH")]
+    convert_out: Option<PathBuf>,
+
    /// Run training mode (train a model and exit)
    #[arg(long)]
    train: bool,
@@ -6221,6 +6232,34 @@ fn vitals_snapshots_from_sensing_json(
    }
 }

+/// Build the multistatic guard config, optionally derived from the TDM schedule
+/// declared in the environment (#1031).
+///
+/// When both `WDP_TDM_SLOTS` and `WDP_TDM_SLOT_US` parse as positive integers,
+/// the guard is derived via [`MultistaticConfig::for_tdm_schedule`] so a
+/// deployment can match its exact schedule. Otherwise the published default
+/// (60 ms hard / 20 ms soft) is returned. `min_nodes` is *not* set here — the
+/// caller overrides it for single-node passthrough.
+fn multistatic_guard_config_from_env() -> MultistaticConfig {
+    multistatic_guard_config_from(
+        std::env::var("WDP_TDM_SLOTS").ok().as_deref(),
+        std::env::var("WDP_TDM_SLOT_US").ok().as_deref(),
+    )
+}
+
+/// Pure core of [`multistatic_guard_config_from_env`] for testability.
+fn multistatic_guard_config_from(slots: Option<&str>, slot_us: Option<&str>) -> MultistaticConfig {
+    match (
+        slots.and_then(|s| s.trim().parse::<usize>().ok()),
+        slot_us.and_then(|s| s.trim().parse::<u64>().ok()),
+    ) {
+        (Some(n), Some(us)) if n >= 1 && us >= 1 => {
+            MultistaticConfig::for_tdm_schedule(n, us)
+        }
+        _ => MultistaticConfig::default(),
+    }
+}
+
 /// Turn a `ProgressiveLoader::new` failure into an actionable diagnostic (#894).
 ///
 /// The published HuggingFace `ruvnet/wifi-densepose-pretrained` files
@@ -6230,6 +6269,11 @@ fn vitals_snapshots_from_sensing_json(
 /// `0x52564653`). Feeding one to `--model` produced a bare
 /// "invalid magic at offset 0 …" that left users stuck. Detect the common
 /// cases and explain plainly what's loadable instead.
+///
+/// Superseded in the live load path by [`load_or_convert_model`] (which now
+/// converts the convertible formats instead of just explaining), but retained
+/// as the human-readable format-landscape summary and exercised by tests.
+#[allow(dead_code)]
 fn diagnose_model_load_error(path: &std::path::Path, data: &[u8], err: &str) -> String {
    let name = path
        .file_name()
@@ -6270,6 +6314,124 @@ fn diagnose_model_load_error(path: &std::path::Path, data: &[u8], err: &str) ->
    )
 }

+/// Load a model for `--model`, auto-detecting + converting the published
+/// HuggingFace formats when the native RVF loader rejects them (issue #894).
+///
+/// Order of operations:
+/// 1. Try the native RVF `ProgressiveLoader` (the only format with `RVFS` magic).
+/// 2. On failure, **auto-detect** the format. If it is convertible
+///    (`safetensors` / `model.rvf.jsonl`), convert it in-memory to RVF and load
+///    that — so the published `model.safetensors` becomes loadable here.
+/// 3. If it is a non-convertible format (quantized blob / unknown), return the
+///    typed, actionable [`model_format::ModelLoadError`] message — never the
+///    opaque "invalid magic …" string.
+///
+/// Returns the loaded `ProgressiveLoader` or a human-actionable error string.
+fn load_or_convert_model(
+    path: &std::path::Path,
+    data: &[u8],
+) -> Result<ProgressiveLoader, String> {
+    use model_format::{convert_to_rvf, detect_format, ModelFormat};
+
+    // 1. Native RVF.
+    if let Ok(loader) = ProgressiveLoader::new(data) {
+        return Ok(loader);
+    }
+
+    let name = path
+        .file_name()
+        .and_then(|n| n.to_str())
+        .unwrap_or("")
+        .to_string();
+    let model_id = path
+        .file_stem()
+        .and_then(|s| s.to_str())
+        .unwrap_or("converted-model");
+
+    match detect_format(data, &name) {
+        // 2. Convertible formats: convert in-memory, then load.
+        ModelFormat::Safetensors | ModelFormat::JsonlManifest => {
+            match convert_to_rvf(data, &name, model_id) {
+                Ok(rvf_bytes) => {
+                    info!(
+                        "Model `{}` is {} — converting to RVF in-memory and loading (issue #894)",
+                        path.display(),
+                        detect_format(data, &name).label()
+                    );
+                    ProgressiveLoader::new(&rvf_bytes).map_err(|e| {
+                        format!(
+                            "converted {} to RVF but the container failed to load: {e}",
+                            detect_format(data, &name).label()
+                        )
+                    })
+                }
+                Err(conv_err) => Err(conv_err.to_string()),
+            }
+        }
+        // 3. Non-convertible: typed actionable error.
+        _ => Err(model_format::classify_load_failure(
+            data,
+            &name,
+            "RVF container parse failed",
+        )
+        .to_string()),
+    }
+}
+
+/// `--convert-model` entry point (issue #894): read `in_path`, convert it to an
+/// RVF binary container, write it to `out_path`, and verify the result loads.
+/// Returns a process exit code (0 = success).
+fn run_convert_model(in_path: &std::path::Path, out_path: &std::path::Path) -> i32 {
+    let data = match std::fs::read(in_path) {
+        Ok(d) => d,
+        Err(e) => {
+            eprintln!("convert-model: failed to read {}: {e}", in_path.display());
+            return 1;
+        }
+    };
+    let name = in_path
+        .file_name()
+        .and_then(|n| n.to_str())
+        .unwrap_or("")
+        .to_string();
+    let model_id = in_path
+        .file_stem()
+        .and_then(|s| s.to_str())
+        .unwrap_or("converted-model");
+
+    let detected = model_format::detect_format(&data, &name);
+    eprintln!(
+        "convert-model: detected {} ({} bytes)",
+        detected.label(),
+        data.len()
+    );
+
+    match model_format::convert_to_rvf(&data, &name, model_id) {
+        Ok(rvf_bytes) => {
+            // Verify the converted bytes actually load before writing.
+            if let Err(e) = ProgressiveLoader::new(&rvf_bytes) {
+                eprintln!("convert-model: produced RVF did NOT load (bug): {e}");
+                return 1;
+            }
+            if let Err(e) = std::fs::write(out_path, &rvf_bytes) {
+                eprintln!("convert-model: failed to write {}: {e}", out_path.display());
+                return 1;
+            }
+            eprintln!(
+                "convert-model: wrote {} ({} bytes). Load it with `--model {}`.",
+                out_path.display(),
+                rvf_bytes.len(),
+                out_path.display()
+            );
+            0
+        }
+        Err(e) => {
+            eprintln!("convert-model: {e}");
+            1
+        }
+    }
+}
+
 /// Whether `--export-rvf` should emit the placeholder container-format demo.
 ///
 /// It must only do so **standalone**. Combined with `--train`/`--pretrain` the
@@ -6323,6 +6485,17 @@ async fn main() {
        return;
    }

+    // Handle --convert-model: turn a published HF model file (safetensors /
+    // model.rvf.jsonl) into the RVF binary container --model expects, then exit
+    // (issue #894). Gives the reporter a one-command path off the heuristics.
+    if let Some(ref in_path) = args.convert_model {
+        let out_path = args
+            .convert_out
+            .clone()
+            .unwrap_or_else(|| in_path.with_extension("rvf"));
+        std::process::exit(run_convert_model(in_path, &out_path));
+    }
+
    // Handle --export-rvf: writes a CONTAINER-FORMAT DEMO with placeholder
    // weights — it is NOT a trained model. Only short-circuit when standalone:
    // combined with --train/--pretrain the real model is exported by the
@@ -6951,7 +7124,7 @@ async fn main() {
        if args.progressive || args.model.is_some() {
            info!("Loading trained model (progressive) from {}", mp.display());
            match std::fs::read(mp) {
-                Ok(data) => match ProgressiveLoader::new(&data) {
+                Ok(data) => match load_or_convert_model(mp, &data) {
                    Ok(mut loader) => {
                        if let Ok(la) = loader.load_layer_a() {
                            info!(
@@ -6963,7 +7136,13 @@ async fn main() {
                        progressive_loader = Some(loader);
                    }
                    Err(e) => {
-                        error!("{}", diagnose_model_load_error(mp, &data, &e.to_string()))
+                        // #894: typed, actionable message (never the opaque magic)
+                        // and a LOUD warning that we are degrading to heuristics.
+                        error!("{e}");
+                        error!(
+                            "Model NOT loaded — falling back to signal heuristics. \
+                             Pose/person-count output will be approximate (issue #894)."
+                        );
                    }
                },
                Err(e) => error!("Failed to read model file: {e}"),
@@ -7136,9 +7315,14 @@ async fn main() {
        pose_tracker: PoseTracker::new(),
        last_tracker_instant: None,
        multistatic_fuser: {
+            // #1031: the default guard (60 ms hard / 20 ms soft) accommodates a
+            // real TDM slot offset. A deployment can override it to match its
+            // own schedule via WDP_TDM_SLOTS + WDP_TDM_SLOT_US (both set ⇒ derive
+            // from the schedule), else the published default is used.
+            let cfg = multistatic_guard_config_from_env();
            let mut fuser = MultistaticFuser::with_config(MultistaticConfig {
                min_nodes: 1, // single-node passthrough
-                ..Default::default()
+                ..cfg
            });
            if let Some(ref pos_str) = args.node_positions {
                let positions = field_bridge::parse_node_positions(pos_str);
@@ -0,0 +1,497 @@
+//! Model-file format detection and conversion (issue #894).
+//!
+//! The published HuggingFace repo `ruvnet/wifi-densepose-pretrained` ships
+//! several files, **none** of which carry the RVF binary-container magic
+//! (`RVFS` = `0x52564653`) that [`crate::rvf_pipeline::ProgressiveLoader`]
+//! expects:
+//!
+//! | File on HF                    | First bytes        | What it is                         |
+//! |-------------------------------|--------------------|------------------------------------|
+//! | `model.safetensors`          | `<u64 LE len>{...` | standard safetensors weight file   |
+//! | `model-q2/q4/q8.bin`         | `35 57 45 77` ("5WEw", LE u32 `0x77455735`) | quantized weight blob |
+//! | `model.rvf.jsonl`            | `{...`             | JSONL manifest (one JSON per line) |
+//! | *(none shipped)*             | `53 46 56 52` ("RVFS"/`RVFS`) | the binary RVF container the loader wants |
+//!
+//! Before this module, feeding any HF file to `--model` produced the opaque
+//! `invalid magic at offset 0: expected 0x52564653, got 0x77455735` and the
+//! server silently fell back to signal heuristics (the "10 persons for 1"
+//! garbage the reporter saw).
+//!
+//! This module:
+//! 1. **Auto-detects** the format by magic + extension ([`detect_format`]).
+//! 2. Returns a **typed, actionable** error ([`ModelLoadError`]) that lists the
+//!    accepted formats and the one-command conversion path — never the opaque
+//!    magic string.
+//! 3. Ships a **converter** ([`safetensors_to_rvf`], [`jsonl_to_rvf`]) so the
+//!    published `model.safetensors` / `model.rvf.jsonl` can be turned into the
+//!    binary RVF container the loader consumes, in one command
+//!    (`sensing-server --convert-model <in> --convert-out <out>`).
+//!
+//! # Honest scope
+//!
+//! Converting `model.safetensors` → RVF wires the **format / load path**: the
+//! safetensors header is parsed, every F32 tensor's weights are flattened into
+//! the RVF `SEG_VEC` weight segment, and a manifest is written so the loader's
+//! Layer A/B/C all succeed. The pose-decoder *architecture* on HF differs from
+//! this crate's inference head, so this converter does **not** claim
+//! end-to-end pose accuracy from the converted weights — it makes the published
+//! model **loadable** (magic/version/segments valid, weights present) and
+//! removes the silent-heuristics fallback. Real pose inference from those exact
+//! weights still needs the matching decoder (tracked in #894).
+
+use crate::rvf_container::RvfBuilder;
+
+/// The RVF binary-container magic, `"RVFS"` as little-endian `u32`.
+const RVFS_MAGIC: u32 = 0x5256_4653;
+/// The quantized-blob magic shipped on HF (`"5WEw"` = bytes `35 57 45 77`),
+/// which decodes to `0x77455735` via `u32::from_le_bytes` — exactly the value
+/// the loader reported in issue #894.
+const HF_QUANT_MAGIC: u32 = 0x7745_5735;
+
+/// A recognised on-disk model-file format.
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+pub enum ModelFormat {
+    /// Native RVF binary container — the loader consumes this directly.
+    Rvf,
+    /// Standard `model.safetensors` (8-byte LE header length + JSON header).
+    Safetensors,
+    /// HuggingFace quantized weight blob (`model-q{2,4,8}.bin`, magic `0x77455735`).
+    HfQuantBin,
+    /// JSONL manifest (`model.rvf.jsonl`) — one JSON object per line.
+    JsonlManifest,
+    /// None of the above.
+    Unknown,
+}
+
+impl ModelFormat {
+    /// Human-readable name for diagnostics.
+    pub fn label(self) -> &'static str {
+        match self {
+            ModelFormat::Rvf => "RVF binary container (RVFS)",
+            ModelFormat::Safetensors => "safetensors weight file",
+            ModelFormat::HfQuantBin => "HuggingFace quantized weight blob (model-q*.bin)",
+            ModelFormat::JsonlManifest => "JSONL manifest (model.rvf.jsonl)",
+            ModelFormat::Unknown => "unknown format",
+        }
+    }
+}
+
+/// A typed, actionable model-load error (issue #894).
+///
+/// Replaces the opaque `"invalid magic at offset 0: expected 0x… got 0x…"`
+/// string with a self-describing variant the caller can match on and present.
+#[derive(Debug, Clone, PartialEq, Eq, thiserror::Error)]
+pub enum ModelLoadError {
+    /// The file is a recognised non-RVF format that must be converted first.
+    #[error(
+        "model file is {detected} — the --model loader needs an RVF binary container. \
+         Convert it once with `sensing-server --convert-model <in> --convert-out model.rvf`, \
+         then load the .rvf. (accepted by --model: RVF binary container; \
+         convertible: safetensors, model.rvf.jsonl)"
+    )]
+    NeedsConversion {
+        /// Label of the detected format.
+        detected: &'static str,
+    },
+
+    /// The file is a quantized HF blob with no in-repo reader.
+    #[error(
+        "model file is a HuggingFace quantized weight blob (magic 0x{magic:08X}); \
+         no reader for this quantization format ships in this build. Use the \
+         full-precision `model.safetensors` from the same HF repo and convert it \
+         with `sensing-server --convert-model model.safetensors --convert-out model.rvf`."
+    )]
+    UnsupportedQuant {
+        /// The magic that was read (e.g. `0x77455735`).
+        magic: u32,
+    },
+
+    /// The file matched no accepted or convertible format.
+    #[error(
+        "model file is an unknown format (first bytes 0x{first_bytes:08X}); \
+         accepted: RVF binary container (RVFS, 0x52564653); convertible: \
+         safetensors, model.rvf.jsonl. ({detail})"
+    )]
+    Unknown {
+        /// The first 4 bytes as a LE u32 (0 if the file is shorter).
+        first_bytes: u32,
+        /// Underlying detail (e.g. the original loader message).
+        detail: String,
+    },
+
+    /// Conversion of a recognised format failed.
+    #[error("failed to convert {format} to RVF: {detail}")]
+    ConversionFailed {
+        /// Source format label.
+        format: &'static str,
+        /// Failure detail.
+        detail: String,
+    },
+}
+
+/// Detect a model-file format from its bytes and optional file name.
+///
+/// Magic bytes take precedence; the `name` (lowercased file name, may be empty)
+/// disambiguates the JSONL/`.bin` cases that share a leading `{`/raw bytes.
+pub fn detect_format(data: &[u8], name: &str) -> ModelFormat {
+    let name = name.to_ascii_lowercase();
+
+    // RVFS magic at offset 0 (the only format the loader reads directly).
+    if leading_u32(data) == Some(RVFS_MAGIC) {
+        return ModelFormat::Rvf;
+    }
+    // safetensors: 8-byte LE header length, then a JSON object opening with '{'.
+    // Checked before the `.bin`/`-q` naming heuristic so a `.safetensors` file
+    // is never mistaken for a quant blob. Validate the declared length is
+    // plausible to avoid false positives.
+    if name.ends_with(".safetensors") || looks_like_safetensors(data) {
+        return ModelFormat::Safetensors;
+    }
+    // HF quantized blob: exact magic, OR `.bin`/`-q` naming.
+    if leading_u32(data) == Some(HF_QUANT_MAGIC) || name.ends_with(".bin") || name.contains("-q") {
+        return ModelFormat::HfQuantBin;
+    }
+    // JSONL manifest: well-known suffix, or a leading '{' that is NOT preceded
+    // by an 8-byte length (already handled above).
+    if name.ends_with(".jsonl") || name.ends_with(".rvf.jsonl") || data.first() == Some(&b'{') {
+        return ModelFormat::JsonlManifest;
+    }
+    ModelFormat::Unknown
+}
+
+/// Map a detected format (for a file that the RVF loader rejected) to a typed,
+/// actionable [`ModelLoadError`]. `detail` carries the original loader message.
+pub fn classify_load_failure(data: &[u8], name: &str, detail: &str) -> ModelLoadError {
+    match detect_format(data, name) {
+        ModelFormat::Rvf => ModelLoadError::Unknown {
+            first_bytes: leading_u32(data).unwrap_or(0),
+            detail: format!("RVFS magic present but container parse failed: {detail}"),
+        },
+        ModelFormat::Safetensors => ModelLoadError::NeedsConversion {
+            detected: ModelFormat::Safetensors.label(),
+        },
+        ModelFormat::JsonlManifest => ModelLoadError::NeedsConversion {
+            detected: ModelFormat::JsonlManifest.label(),
+        },
+        ModelFormat::HfQuantBin => ModelLoadError::UnsupportedQuant {
+            magic: leading_u32(data).unwrap_or(HF_QUANT_MAGIC),
+        },
+        ModelFormat::Unknown => ModelLoadError::Unknown {
+            first_bytes: leading_u32(data).unwrap_or(0),
+            detail: detail.to_string(),
+        },
+    }
+}
+
+/// Convert a `model.safetensors` byte buffer into an RVF binary container that
+/// [`crate::rvf_pipeline::ProgressiveLoader`] can load (issue #894).
+///
+/// Every `F32` tensor in the safetensors file is flattened (in header order)
+/// into the RVF `SEG_VEC` weight segment; a manifest records provenance. The
+/// returned bytes start with the `RVFS` magic and load cleanly.
+///
+/// # Errors
+/// [`ModelLoadError::ConversionFailed`] if the safetensors header is malformed,
+/// or [`ModelLoadError::NeedsConversion`]-shaped detail if no F32 tensors exist.
+pub fn safetensors_to_rvf(data: &[u8], model_id: &str) -> Result<Vec<u8>, ModelLoadError> {
+    let fail = |d: String| ModelLoadError::ConversionFailed {
+        format: ModelFormat::Safetensors.label(),
+        detail: d,
+    };
+
+    if data.len() < 8 {
+        return Err(fail("file shorter than the 8-byte safetensors length header".into()));
+    }
+    let header_len = u64::from_le_bytes(data[0..8].try_into().unwrap()) as usize;
+    let header_start: usize = 8;
+    let header_end = header_start
+        .checked_add(header_len)
+        .filter(|&e| e <= data.len())
+        .ok_or_else(|| fail(format!("declared header length {header_len} exceeds file size")))?;
+
+    let header: serde_json::Value = serde_json::from_slice(&data[header_start..header_end])
+        .map_err(|e| fail(format!("safetensors header is not valid JSON: {e}")))?;
+    let obj = header
+        .as_object()
+        .ok_or_else(|| fail("safetensors header is not a JSON object".into()))?;
+
+    let tensor_base = header_end;
+    let mut weights: Vec<f32> = Vec::new();
+    let mut tensor_names: Vec<String> = Vec::new();
+
+    // Iterate tensors in a stable (sorted) order for deterministic output.
+    let mut entries: Vec<(&String, &serde_json::Value)> = obj
+        .iter()
+        .filter(|(k, _)| k.as_str() != "__metadata__")
+        .collect();
+    entries.sort_by(|a, b| a.0.cmp(b.0));
+
+    for (tname, tinfo) in entries {
+        let dtype = tinfo.get("dtype").and_then(|d| d.as_str()).unwrap_or("");
+        // Only F32 is decoded into the weight vector. Other dtypes are recorded
+        // in the manifest but not flattened (honest: we do not silently cast).
+        let offsets = tinfo
+            .get("data_offsets")
+            .and_then(|o| o.as_array())
+            .and_then(|a| {
+                Some((a.first()?.as_u64()? as usize, a.get(1)?.as_u64()? as usize))
+            });
+        let Some((start, end)) = offsets else { continue };
+        let abs_start = tensor_base.checked_add(start);
+        let abs_end = tensor_base.checked_add(end);
+        match (abs_start, abs_end) {
+            (Some(s), Some(e)) if e <= data.len() && s <= e => {
+                if dtype == "F32" {
+                    let bytes = &data[s..e];
+                    if bytes.len() % 4 == 0 {
+                        for chunk in bytes.chunks_exact(4) {
+                            weights.push(f32::from_le_bytes([
+                                chunk[0], chunk[1], chunk[2], chunk[3],
+                            ]));
+                        }
+                        tensor_names.push(tname.clone());
+                    }
+                }
+            }
+            _ => {
+                return Err(fail(format!(
+                    "tensor `{tname}` data_offsets [{start}..{end}] out of bounds"
+                )));
+            }
+        }
+    }
+
+    if weights.is_empty() {
+        return Err(fail(
+            "no F32 tensors found to convert (the published weights may be quantized; \
+             use a full-precision safetensors export)"
+                .into(),
+        ));
+    }
+
+    let mut builder = RvfBuilder::new();
+    builder.add_manifest(
+        model_id,
+        "converted-from-safetensors",
+        "RVF container converted from model.safetensors (issue #894)",
+    );
+    builder.add_weights(&weights);
+    builder.add_metadata(&serde_json::json!({
+        "source_format": "safetensors",
+        "converted_tensors": tensor_names,
+        "n_weights": weights.len(),
+        "note": "weights loaded; pose-decoder architecture may differ — see #894",
+    }));
+    Ok(builder.build())
+}
+
+/// Convert a `model.rvf.jsonl` byte buffer into an RVF binary container.
+///
+/// The JSONL manifest is one JSON object per line. This wraps the parsed lines
+/// into an RVF manifest + metadata so the file becomes loadable; any numeric
+/// `weights` array found on a line is flattened into the weight segment.
+///
+/// # Errors
+/// [`ModelLoadError::ConversionFailed`] if no line parses as JSON.
+pub fn jsonl_to_rvf(data: &[u8], model_id: &str) -> Result<Vec<u8>, ModelLoadError> {
+    let fail = |d: String| ModelLoadError::ConversionFailed {
+        format: ModelFormat::JsonlManifest.label(),
+        detail: d,
+    };
+    let text = std::str::from_utf8(data).map_err(|e| fail(format!("not valid UTF-8: {e}")))?;
+
+    let mut lines: Vec<serde_json::Value> = Vec::new();
+    let mut weights: Vec<f32> = Vec::new();
+    for line in text.lines() {
+        let line = line.trim();
+        if line.is_empty() {
+            continue;
+        }
+        let v: serde_json::Value = serde_json::from_str(line)
+            .map_err(|e| fail(format!("line is not valid JSON: {e}")))?;
+        if let Some(arr) = v.get("weights").and_then(|w| w.as_array()) {
+            for x in arr {
+                if let Some(f) = x.as_f64() {
+                    weights.push(f as f32);
+                }
+            }
+        }
+        lines.push(v);
+    }
+    if lines.is_empty() {
+        return Err(fail("manifest contained no JSON lines".into()));
+    }
+
+    let mut builder = RvfBuilder::new();
+    builder.add_manifest(
+        model_id,
+        "converted-from-jsonl",
+        "RVF container converted from model.rvf.jsonl (issue #894)",
+    );
+    if !weights.is_empty() {
+        builder.add_weights(&weights);
+    }
+    builder.add_metadata(&serde_json::json!({
+        "source_format": "rvf.jsonl",
+        "n_lines": lines.len(),
+        "n_weights": weights.len(),
+    }));
+    Ok(builder.build())
+}
+
+/// Convert any *convertible* model file to RVF bytes, auto-detecting the format.
+///
+/// Used by the `--convert-model` CLI seam. Returns the converted RVF bytes, or a
+/// typed error for formats that cannot be converted (quantized blobs, unknown).
+pub fn convert_to_rvf(data: &[u8], name: &str, model_id: &str) -> Result<Vec<u8>, ModelLoadError> {
+    match detect_format(data, name) {
+        ModelFormat::Rvf => Ok(data.to_vec()), // already RVF — pass through.
+        ModelFormat::Safetensors => safetensors_to_rvf(data, model_id),
+        ModelFormat::JsonlManifest => jsonl_to_rvf(data, model_id),
+        ModelFormat::HfQuantBin => Err(ModelLoadError::UnsupportedQuant {
+            magic: leading_u32(data).unwrap_or(HF_QUANT_MAGIC),
+        }),
+        ModelFormat::Unknown => Err(ModelLoadError::Unknown {
+            first_bytes: leading_u32(data).unwrap_or(0),
+            detail: "not a convertible model format".into(),
+        }),
+    }
+}
+
+// ── helpers ─────────────────────────────────────────────────────────────────
+
+fn leading_u32(data: &[u8]) -> Option<u32> {
+    data.get(0..4)
+        .map(|b| u32::from_le_bytes([b[0], b[1], b[2], b[3]]))
+}
+
+/// A safetensors file: first 8 bytes are a LE u64 header length, byte 8 is `{`,
+/// and the declared length must fit within the buffer (or be a plausible prefix).
+fn looks_like_safetensors(data: &[u8]) -> bool {
+    if data.len() < 9 || data[8] != b'{' {
+        return false;
+    }
+    let header_len = u64::from_le_bytes(data[0..8].try_into().unwrap());
+    // A real header is non-trivial and bounded; reject absurd lengths that would
+    // indicate this is actually some other binary that happens to have a '{' at
+    // byte 8. Allow the case where we only have the header prefix (len > data).
+    header_len >= 2 && header_len <= 64 * 1024 * 1024
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::rvf_pipeline::ProgressiveLoader;
+
+    /// Build a minimal valid safetensors buffer with one F32 tensor.
+    fn make_safetensors(weights: &[f32]) -> Vec<u8> {
+        let n = weights.len();
+        let header = serde_json::json!({
+            "weight": {
+                "dtype": "F32",
+                "shape": [n],
+                "data_offsets": [0, n * 4],
+            }
+        });
+        let header_bytes = serde_json::to_vec(&header).unwrap();
+        let mut out = Vec::new();
+        out.extend_from_slice(&(header_bytes.len() as u64).to_le_bytes());
+        out.extend_from_slice(&header_bytes);
+        for &w in weights {
+            out.extend_from_slice(&w.to_le_bytes());
+        }
+        out
+    }
+
+    #[test]
+    fn detects_safetensors_by_magic_and_name() {
+        let st = make_safetensors(&[1.0, 2.0, 3.0]);
+        assert_eq!(detect_format(&st, "model.safetensors"), ModelFormat::Safetensors);
+        assert_eq!(detect_format(&st, ""), ModelFormat::Safetensors); // by content
+    }
+
+    #[test]
+    fn detects_hf_quant_magic() {
+        // The exact bytes the loader reported: "5WEw" => LE u32 0x77455735.
+        let data = [0x35u8, 0x57, 0x45, 0x77, 0xAA, 0xBB];
+        assert_eq!(leading_u32(&data), Some(HF_QUANT_MAGIC));
+        assert_eq!(detect_format(&data, "model-q4.bin"), ModelFormat::HfQuantBin);
+        assert_eq!(detect_format(&data, ""), ModelFormat::HfQuantBin); // by magic
+    }
+
+    #[test]
+    fn detects_jsonl_and_rvf() {
+        assert_eq!(detect_format(b"{\"seg\":0}\n", "model.rvf.jsonl"), ModelFormat::JsonlManifest);
+        // RVFS magic ("RVFS" LE) -> Rvf.
+        let rvfs = RVFS_MAGIC.to_le_bytes();
+        assert_eq!(detect_format(&rvfs, "model.rvf"), ModelFormat::Rvf);
+    }
+
+    /// CORE #894 PROOF: the published safetensors converts to a container the
+    /// ProgressiveLoader loads (Layer A succeeds, weights present) — the old
+    /// path returned the opaque "invalid magic … 0x77455735" and gave up.
+    #[test]
+    fn safetensors_converts_and_loads() {
+        let st = make_safetensors(&[1.0, 2.0, 3.0, 4.0]);
+        let rvf = safetensors_to_rvf(&st, "wifi-densepose-pretrained")
+            .expect("safetensors must convert to RVF");
+        // The converted bytes carry the RVFS magic.
+        assert_eq!(leading_u32(&rvf), Some(RVFS_MAGIC));
+        // And the ProgressiveLoader actually loads it.
+        let mut loader = ProgressiveLoader::new(&rvf).expect("converted RVF must load");
+        let la = loader.load_layer_a().expect("Layer A");
+        assert_eq!(la.model_name, "wifi-densepose-pretrained");
+        let lc = loader.load_layer_c().expect("Layer C");
+        assert_eq!(lc.all_weights, vec![1.0, 2.0, 3.0, 4.0], "weights round-trip");
+    }
+
+    /// CORE #894 PROOF: feeding the HF quant magic to the classifier yields the
+    /// new actionable typed error — never the opaque magic panic.
+    #[test]
+    fn hf_quant_classifies_to_actionable_error() {
+        let data = [0x35u8, 0x57, 0x45, 0x77];
+        let err = classify_load_failure(
+            &data,
+            "model-q4.bin",
+            "invalid magic at offset 0: expected 0x52564653, got 0x77455735",
+        );
+        assert!(matches!(err, ModelLoadError::UnsupportedQuant { magic } if magic == HF_QUANT_MAGIC));
+        let msg = err.to_string();
+        assert!(msg.contains("safetensors"), "must point at the loadable format: {msg}");
+        assert!(!msg.contains("invalid magic at offset"), "must not leak opaque magic: {msg}");
+    }
+
+    /// safetensors load failure is classified as NeedsConversion with a
+    /// one-command path — not the opaque magic.
+    #[test]
+    fn safetensors_classifies_to_needs_conversion() {
+        let st = make_safetensors(&[1.0]);
+        let err = classify_load_failure(&st, "model.safetensors", "invalid magic …");
+        assert!(matches!(err, ModelLoadError::NeedsConversion { .. }));
+        let msg = err.to_string();
+        assert!(msg.contains("--convert-model"), "must give the convert command: {msg}");
+    }
+
+    /// jsonl manifest converts and loads.
+    #[test]
+    fn jsonl_converts_and_loads() {
+        let jsonl = b"{\"model_id\":\"x\"}\n{\"weights\":[1.0,2.0]}\n";
+        let rvf = jsonl_to_rvf(jsonl, "x").expect("jsonl converts");
+        let mut loader = ProgressiveLoader::new(&rvf).expect("converted jsonl loads");
+        let _ = loader.load_layer_a().expect("Layer A");
+        let lc = loader.load_layer_c().expect("Layer C");
+        assert_eq!(lc.all_weights, vec![1.0, 2.0]);
+    }
+
+    /// convert_to_rvf dispatches by detected format and rejects quant blobs.
+    #[test]
+    fn convert_to_rvf_dispatches_and_rejects_quant() {
+        let st = make_safetensors(&[5.0]);
+        assert!(convert_to_rvf(&st, "model.safetensors", "m").is_ok());
+        let quant = [0x35u8, 0x57, 0x45, 0x77];
+        assert!(matches!(
+            convert_to_rvf(&quant, "model-q4.bin", "m"),
+            Err(ModelLoadError::UnsupportedQuant { .. })
+        ));
+    }
+}
@@ -84,11 +84,32 @@ pub struct FusedSensingFrame {
 #[derive(Debug, Clone)]
 pub struct MultistaticConfig {
    /// Maximum timestamp spread (microseconds) across nodes in one cycle.
-    /// Default: 5000 us (5 ms), well within the 50 ms TDMA cycle.
+    ///
+    /// # Derivation from the TDM schedule (issue #1031)
+    ///
+    /// In an N-slot TDMA mesh, node `k` transmits in slot `k`, so two nodes
+    /// are *deliberately* separated by `(cycle_us × slot_fraction)`. On a real
+    /// 2-node mesh (slots 0 and 1 of a ~36 ms cycle) we measured an
+    /// **18,194 µs** spread between paired frames — i.e. the spread is the slot
+    /// offset, NOT clock jitter. The previous 5,000 µs default therefore
+    /// rejected every real frame set and fusion silently fell back to per-node
+    /// sum/dedup, so multistatic fusion never actually ran on hardware.
+    ///
+    /// The default is now **60,000 µs (60 ms)**: a full 50 ms TDMA cycle (the
+    /// worst-case spread for the last slot of a maximally-loaded schedule) plus
+    /// ~20% headroom for inter-cycle scheduling jitter. This accepts a real
+    /// N-node cycle as coherent while still rejecting a spread that exceeds one
+    /// whole cycle (which would mean frames from *different* sensing cycles were
+    /// mixed). Tune per deployment with [`MultistaticConfig::for_tdm_schedule`].
    pub guard_interval_us: u64,
    /// ADR-137 soft guard (microseconds): a spread above this but within
    /// `guard_interval_us` is fused but recorded as a `TimestampMismatch`
-    /// contradiction (loose alignment ⇒ privacy demotion). Default guard/5.
+    /// contradiction (loose alignment ⇒ privacy demotion).
+    ///
+    /// Set to **20,000 µs (20 ms)**: just above the observed 18,194 µs 2-slot
+    /// spread, so a normal 2-node cycle fuses *cleanly* (no demotion), but a
+    /// spread approaching a full cycle is flagged as loose alignment. Kept below
+    /// `guard_interval_us` so the soft band is meaningful.
    pub soft_guard_us: u64,
    /// Minimum number of nodes for multistatic mode.
    /// Falls back to single-node mode if fewer nodes are available.
@@ -106,8 +127,11 @@ pub struct MultistaticConfig {
 impl Default for MultistaticConfig {
    fn default() -> Self {
        Self {
-            guard_interval_us: 5000,
-            soft_guard_us: 1000,
+            // 60 ms hard / 20 ms soft — see field docs for the TDM derivation
+            // (issue #1031). The old 5 ms hard guard rejected every real frame
+            // set (observed 2-slot spread ≈ 18.2 ms), silently disabling fusion.
+            guard_interval_us: 60_000,
+            soft_guard_us: 20_000,
            min_nodes: 2,
            attention_temperature: 1.0,
            enable_person_separation: true,
@@ -116,6 +140,43 @@ impl Default for MultistaticConfig {
    }
 }

+impl MultistaticConfig {
+    /// Derive a guard interval from an explicit TDM schedule (issue #1031).
+    ///
+    /// In an N-slot schedule with per-slot duration `slot_duration_us`, the
+    /// maximum legitimate spread between two paired node frames in one cycle is
+    /// the full cycle length `tdm_total_slots × slot_duration_us` (last slot vs
+    /// first slot). The hard guard is set to that cycle length plus 20% jitter
+    /// headroom; the soft guard to ~⅓ of the cycle (a normal adjacent-slot pair
+    /// fuses cleanly, a near-full-cycle spread is flagged as loose alignment).
+    ///
+    /// `tdm_total_slots` is clamped to ≥ 1. All other fields take their
+    /// [`Default`] values.
+    ///
+    /// # Example
+    /// ```
+    /// use wifi_densepose_signal::ruvsense::multistatic::MultistaticConfig;
+    /// // 2 slots × 18 ms = 36 ms cycle → ~43 ms hard guard accepts the
+    /// // reported 18,194 µs 2-slot spread.
+    /// let cfg = MultistaticConfig::for_tdm_schedule(2, 18_000);
+    /// assert!(cfg.guard_interval_us >= 18_194);
+    /// ```
+    #[must_use]
+    pub fn for_tdm_schedule(tdm_total_slots: usize, slot_duration_us: u64) -> Self {
+        let slots = tdm_total_slots.max(1) as u64;
+        let cycle_us = slots.saturating_mul(slot_duration_us);
+        // +20% jitter headroom on the full cycle.
+        let guard_interval_us = cycle_us.saturating_add(cycle_us / 5).max(1);
+        // Soft band at ~⅓ cycle, kept strictly below the hard guard.
+        let soft_guard_us = (cycle_us / 3).clamp(1, guard_interval_us.saturating_sub(1).max(1));
+        Self {
+            guard_interval_us,
+            soft_guard_us,
+            ..Default::default()
+        }
+    }
+}
+
 /// Multistatic frame fuser.
 ///
 /// Collects per-node multi-band frames and produces a single fused
@@ -825,21 +886,87 @@ mod tests {
    #[test]
    fn ac_fuse_scored_loose_alignment_flags_soft_contradiction() {
        use super::super::fusion_quality::ContradictionFlag;
-        // guard 5000 us; spread 2000 us is within guard but > soft_guard 1000 us.
+        // Default soft_guard is now 20_000 us (#1031). A spread above soft but
+        // within the 60_000 us hard guard is fused yet flagged as loose. Use a
+        // 25_000 us spread: > soft (20 ms), < hard (60 ms).
        let fuser = MultistaticFuser::new();
-        let f0 = make_node_frame(0, 1000, 56, 1.0);
-        let f1 = make_node_frame(1, 3000, 56, 1.0);
+        let f0 = make_node_frame(0, 1_000, 56, 1.0);
+        let f1 = make_node_frame(1, 26_000, 56, 1.0);
        let (_fused, score) = fuser.fuse_scored(&[f0, f1], 0.85).unwrap();

        assert!(score.forces_privacy_demotion(), "loose alignment ⇒ demotion");
        assert!(matches!(
            score.contradiction_flags[0],
-            ContradictionFlag::TimestampMismatch { spread_ns: 2_000_000, soft_guard_ns: 1_000_000 }
+            ContradictionFlag::TimestampMismatch { spread_ns: 25_000_000, soft_guard_ns: 20_000_000 }
        ));
        // Penalized coherence is strictly below base when a contradiction fires.
        assert!(score.penalized_coherence() < score.base_coherence);
    }

+    /// REGRESSION (issue #1031): a real 2-node TDM frame set with an 18,194 µs
+    /// spread (the reported value) must FUSE under the default config — the old
+    /// 5,000 µs guard rejected it with `TimestampMismatch`, silently disabling
+    /// multistatic fusion on every real deployment.
+    #[test]
+    fn fuse_real_tdm_spread_18194us_fuses_with_default_guard() {
+        let fuser = MultistaticFuser::new(); // default config
+        let f0 = make_node_frame(0, 1_000, 56, 1.0);
+        let f1 = make_node_frame(1, 1_000 + 18_194, 56, 1.0);
+        let fused = fuser
+            .fuse(&[f0, f1])
+            .expect("18,194 us 2-slot spread must fuse under the #1031 default guard");
+        assert_eq!(fused.active_nodes, 2, "both nodes contribute (real fusion)");
+        // The 18.2 ms spread is below the soft guard (20 ms), so fuse_scored
+        // records it as a CLEAN fuse (no privacy demotion) — the common case.
+        let f0b = make_node_frame(0, 1_000, 56, 1.0);
+        let f1b = make_node_frame(1, 1_000 + 18_194, 56, 1.0);
+        let (_f, score) = fuser.fuse_scored(&[f0b, f1b], 0.85).unwrap();
+        assert!(
+            !score.forces_privacy_demotion(),
+            "a normal 2-slot spread (18.2 ms < 20 ms soft) must NOT demote privacy"
+        );
+    }
+
+    /// The guard still does its job: a spread larger than a whole TDM cycle
+    /// (frames from different cycles) is rejected. Uses a tight per-deployment
+    /// config derived from the schedule via `for_tdm_schedule`.
+    #[test]
+    fn configurable_guard_rejects_too_large_spread() {
+        // 2 slots × 18 ms = 36 ms cycle → ~43 ms hard guard.
+        let cfg = MultistaticConfig::for_tdm_schedule(2, 18_000);
+        assert!(
+            cfg.guard_interval_us >= 18_194,
+            "derived guard must accept the reported 2-slot spread: {}",
+            cfg.guard_interval_us
+        );
+        let fuser = MultistaticFuser::with_config(cfg.clone());
+        // A spread well beyond a full cycle (e.g. 2× the hard guard) is rejected.
+        let too_large = cfg.guard_interval_us * 2;
+        let f0 = make_node_frame(0, 0, 56, 1.0);
+        let f1 = make_node_frame(1, too_large, 56, 1.0);
+        assert!(
+            matches!(
+                fuser.fuse(&[f0, f1]),
+                Err(MultistaticError::TimestampMismatch { .. })
+            ),
+            "a spread beyond a full TDM cycle must still be rejected"
+        );
+    }
+
+    /// The derived soft guard stays strictly below the hard guard, and a
+    /// degenerate (0-slot) schedule clamps to a usable config.
+    #[test]
+    fn for_tdm_schedule_invariants() {
+        let cfg = MultistaticConfig::for_tdm_schedule(4, 12_500); // 50 ms cycle
+        assert!(cfg.soft_guard_us < cfg.guard_interval_us);
+        assert!(cfg.guard_interval_us >= 50_000);
+        // Degenerate input clamps instead of producing a zero/overflow guard.
+        let degenerate = MultistaticConfig::for_tdm_schedule(0, 0);
+        assert!(degenerate.guard_interval_us >= 1);
+        assert!(degenerate.soft_guard_us >= 1);
+        assert!(degenerate.soft_guard_us < degenerate.guard_interval_us.max(2));
+    }
+
    #[test]
    fn ac_fuse_scored_calibrated_agreement_sets_id() {
        use super::super::fusion_quality::{CalibrationId, EvidenceRef};
@@ -996,7 +1123,11 @@ mod tests {
    #[test]
    fn default_config() {
        let cfg = MultistaticConfig::default();
-        assert_eq!(cfg.guard_interval_us, 5000);
+        // #1031: hard guard raised to 60 ms (was 5 ms) to accommodate the real
+        // TDM slot offset; soft guard 20 ms, both strictly ordered.
+        assert_eq!(cfg.guard_interval_us, 60_000);
+        assert_eq!(cfg.soft_guard_us, 20_000);
+        assert!(cfg.soft_guard_us < cfg.guard_interval_us);
        assert_eq!(cfg.min_nodes, 2);
        assert!((cfg.attention_temperature - 1.0).abs() < f32::EPSILON);
        assert!(cfg.enable_person_separation);
@@ -0,0 +1,108 @@
+//! Runnable demo of the unified [`EdgePipeline`]: constructs every registered
+//! skill, feeds a short deterministic synthetic CSI frame sequence, and prints
+//! the per-skill events plus a registration summary.
+//!
+//! ```bash
+//! cd v2/crates/wifi-densepose-wasm-edge
+//! cargo run --example run_all_skills --features std
+//! cargo run --example run_all_skills --features std,medical-experimental
+//! ```
+//!
+//! [`EdgePipeline`]: wifi_densepose_wasm_edge::pipeline_all::EdgePipeline
+
+#[cfg(not(feature = "std"))]
+fn main() {
+    eprintln!("run_all_skills requires --features std");
+}
+
+#[cfg(feature = "std")]
+fn main() {
+    use std::collections::BTreeMap;
+    use wifi_densepose_wasm_edge::pipeline_all::{CsiFrameView, EdgePipeline};
+
+    const N_SC: usize = 32;
+    let mut pipeline = EdgePipeline::new();
+
+    println!("=== EdgePipeline registration ===");
+    println!("registered skills: {}", pipeline.skill_count());
+    let med = pipeline
+        .skills()
+        .iter()
+        .filter(|s| s.medical_experimental)
+        .count();
+    println!(
+        "  default tier: {}   medical-experimental tier: {}",
+        pipeline.skill_count() - med,
+        med
+    );
+    println!();
+
+    let mut phases = [0.0f32; N_SC];
+    let mut amps = [0.0f32; N_SC];
+    let mut vars = [0.0f32; N_SC];
+    let mut prev = [0.0f32; N_SC];
+
+    // Per-skill event counters over the run.
+    let mut counts: BTreeMap<&'static str, usize> = BTreeMap::new();
+    for s in pipeline.skills() {
+        counts.insert(s.name, 0);
+    }
+
+    let frames = 300usize;
+    for t in 0..frames {
+        let tf = t as f32;
+        let breath = (tf * 2.0 * std::f32::consts::PI * 0.3 / 20.0).sin();
+        let heart = (tf * 2.0 * std::f32::consts::PI * 1.2 / 20.0).sin();
+        let mut vmean = 0.0f32;
+        for i in 0..N_SC {
+            let sc = i as f32;
+            phases[i] = (sc * 0.21 + tf * 0.05).sin() + 0.15 * breath;
+            amps[i] = 1.0 + 0.3 * (sc * 0.11 + tf * 0.03).cos() + 0.1 * heart;
+            vars[i] = 0.02 + 0.01 * (sc * 0.3).sin().abs()
+                + if (t / 40) % 2 == 0 { 0.05 } else { 0.0 };
+            vmean += vars[i];
+        }
+        vmean /= N_SC as f32;
+
+        let v = CsiFrameView {
+            phases: &phases,
+            amplitudes: &amps,
+            variances: &vars,
+            prev_phases: &prev,
+            presence: if (t / 30) % 3 == 0 { 0 } else { 1 },
+            n_persons: ((t / 50) % 3) as i32,
+            motion_energy: 0.3 + 0.2 * (tf * 0.07).sin().abs(),
+            breathing_bpm: 18.0 + 2.0 * (tf * 0.01).sin(),
+            heartrate_bpm: 72.0 + 5.0 * (tf * 0.02).sin(),
+            coherence: 0.5 + 0.4 * (tf * 0.03).cos(),
+            variance_mean: vmean,
+        };
+
+        for e in pipeline.on_frame(&v) {
+            *counts.entry(e.skill).or_insert(0) += 1;
+            // Print the first few events from the last frame to show liveness.
+            if t == frames - 1 {
+                println!(
+                    "  frame {} | {:<26} event {:>3} = {:.4}",
+                    t, e.skill, e.event_id, e.value
+                );
+            }
+        }
+        prev.copy_from_slice(&phases);
+    }
+
+    println!();
+    println!("=== per-skill event totals over {} synthetic frames ===", frames);
+    let total: usize = counts.values().sum();
+    let active = counts.values().filter(|&&c| c > 0).count();
+    for (name, c) in &counts {
+        println!("  {:<28} {}", name, c);
+    }
+    println!();
+    println!(
+        "TOTAL events: {}   skills that emitted at least once: {}/{}",
+        total,
+        active,
+        pipeline.skill_count()
+    );
+}
@@ -94,6 +94,18 @@ pub mod ind_structural_vibration;

 pub mod vendor_common;

+// ── Unified edge pipeline (ADR-160 deliverable) ──────────────────────────────
+//
+// `EdgePipeline` registers EVERY runtime skill module behind one uniform
+// `EdgeSkill` trait and runs them all per CSI frame. Host-only (`std`): it uses
+// Box/Vec for dynamic dispatch; the wasm `no_std` build keeps the small flagship
+// pipeline in this file. The `med_*` tier is registered only under
+// `medical-experimental` (preserves the ADR-160 safety gate).
+#[cfg(feature = "std")]
+pub mod pipeline_all;
+#[cfg(feature = "std")]
+pub mod skill_registry;
+
 // ── Vendor-integrated modules (ADR-041 Category 7) ──────────────────────────
 //
 // 24 modules organised into 7 sub-categories.  Each module file lives in
@@ -0,0 +1,217 @@
+//! Unified edge pipeline — registers **every** runtime skill module in the crate
+//! behind one uniform [`EdgeSkill`] trait and runs them all per CSI frame.
+//!
+//! # Why this module exists
+//!
+//! Each skill in `src/*.rs` is an independently-loadable DSP module with its own
+//! bespoke `process_frame` / `on_timer` signature (some take `&[f32]` phases,
+//! some scalars like `motion_energy`, some `breathing_bpm`/`heartrate_bpm`, etc.).
+//! On the wasm target only the flagship `gesture + coherence + adversarial`
+//! pipeline (in `lib.rs`) is on the default `on_frame` path. This module wires
+//! **all** of them into a single [`EdgePipeline`] so a host can run the whole
+//! skill library over one CSI frame stream and collect every emitted event,
+//! tagged by its source skill.
+//!
+//! # Design
+//!
+//! - [`CsiFrameView`] — a borrowed, host-supplied view of one CSI frame carrying
+//!   every input any skill needs (phase/amplitude/variance slices + the scalar
+//!   features the host derives: presence, n_persons, motion_energy, breathing &
+//!   heart rate, coherence, plus the previous frame's phases for delta skills).
+//! - [`EdgeSkill`] — the uniform adapter trait. Each skill gets a small adapter
+//!   (see `skill_registry`) that pulls the fields it needs out of the view, calls
+//!   the underlying detector **unchanged**, and returns an aggregated
+//!   `&[(i32, f32)]` event buffer. **No skill DSP is modified.**
+//! - [`EdgePipeline`] — owns one boxed adapter per skill, dispatches `on_frame`
+//!   to all of them, and aggregates `(skill_name, event_id, value)` triples.
+//!
+//! # Feature gating (preserves the ADR-160 safety gate)
+//!
+//! The five `med_*` skills are registered **only** under
+//! `--features medical-experimental`. They are NOT pulled into the default
+//! pipeline, so they cannot be silently built into a shipping artifact. The
+//! medical tier is opt-in; see `EdgePipeline::new` and `skills()`.
+//!
+//! Requires `std` (uses `Box`/`Vec`); the wasm `no_std` build keeps the small
+//! flagship `lib.rs` pipeline instead.
+
+#![cfg(feature = "std")]
+
+extern crate std;
+use std::boxed::Box;
+use std::vec::Vec;
+
+/// Borrowed view of one CSI frame: every input any registered skill can consume.
+///
+/// The host derives these from the Tier-2 DSP output. Slices are
+/// per-subcarrier; scalars are frame-level aggregates. A skill adapter reads
+/// only the fields it needs and ignores the rest — heterogeneity is absorbed
+/// here, not in the skills.
+#[derive(Clone, Copy)]
+pub struct CsiFrameView<'a> {
+    /// Per-subcarrier unwrapped phase (radians).
+    pub phases: &'a [f32],
+    /// Per-subcarrier amplitude (linear).
+    pub amplitudes: &'a [f32],
+    /// Per-subcarrier short-window variance.
+    pub variances: &'a [f32],
+    /// Previous frame's phases (for delta/velocity skills like the spiking tracker).
+    pub prev_phases: &'a [f32],
+    /// Presence flag from host (0 = empty, 1 = occupied).
+    pub presence: i32,
+    /// Estimated person count from host.
+    pub n_persons: i32,
+    /// Frame-level motion energy.
+    pub motion_energy: f32,
+    /// Breathing rate estimate (breaths/min); 0 if unavailable.
+    pub breathing_bpm: f32,
+    /// Heart rate estimate (beats/min); 0 if unavailable.
+    pub heartrate_bpm: f32,
+    /// Coherence score [0,1] from the coherence monitor (for gate-style skills).
+    pub coherence: f32,
+    /// Mean variance across `variances` (convenience scalar for skills wanting one).
+    pub variance_mean: f32,
+}
+
+impl<'a> CsiFrameView<'a> {
+    /// Mean amplitude across the frame (convenience for scalar-input skills).
+    #[inline]
+    pub fn amplitude_mean(&self) -> f32 {
+        if self.amplitudes.is_empty() {
+            return 0.0;
+        }
+        let mut s = 0.0f32;
+        for &a in self.amplitudes {
+            s += a;
+        }
+        s / self.amplitudes.len() as f32
+    }
+
+    /// Mean phase across the frame.
+    #[inline]
+    pub fn phase_mean(&self) -> f32 {
+        if self.phases.is_empty() {
+            return 0.0;
+        }
+        let mut s = 0.0f32;
+        for &p in self.phases {
+            s += p;
+        }
+        s / self.phases.len() as f32
+    }
+}
+
+/// One emitted event, tagged by its source skill.
+#[derive(Clone, Copy, Debug, PartialEq)]
+pub struct SkillEvent {
+    /// Stable name of the skill that produced this event (e.g. `"occupancy"`).
+    pub skill: &'static str,
+    /// Event type id (the registry id from `event_types`).
+    pub event_id: i32,
+    /// Event payload value.
+    pub value: f32,
+}
+
+/// Uniform adapter trait over a heterogeneous skill detector.
+///
+/// Implementors live in `skill_registry`; each wraps exactly one underlying
+/// detector and forwards `on_frame` to its real `process_frame`/`on_timer`
+/// without changing the DSP. `event_ids()` is introspection only.
+pub trait EdgeSkill {
+    /// Stable skill name (matches the `src/<name>.rs` module).
+    fn name(&self) -> &'static str;
+    /// The event ids this skill can emit (for introspection / docs).
+    fn event_ids(&self) -> &'static [i32];
+    /// Run this skill over one frame, returning its emitted `(event_id, value)`
+    /// pairs. Returns an empty slice if the skill emitted nothing this frame.
+    fn on_frame(&mut self, frame: &CsiFrameView) -> &[(i32, f32)];
+}
+
+/// Introspection record for one registered skill.
+#[derive(Clone, Copy, Debug)]
+pub struct SkillInfo {
+    /// Skill name.
+    pub name: &'static str,
+    /// Event ids the skill can emit.
+    pub event_ids: &'static [i32],
+    /// Whether the skill is part of the gated `medical-experimental` tier.
+    pub medical_experimental: bool,
+}
+
+/// The unified pipeline: holds one adapter per registered skill and runs them
+/// all per frame.
+pub struct EdgePipeline {
+    skills: Vec<Box<dyn EdgeSkill>>,
+    /// Parallel flag marking which entries are the gated medical tier.
+    medical_flags: Vec<bool>,
+    frame_count: u64,
+}
+
+impl EdgePipeline {
+    /// Construct the pipeline with **every** registered skill.
+    ///
+    /// The five `med_*` skills are included **only** when the crate is built
+    /// with `--features medical-experimental`; otherwise the default
+    /// (non-medical) tier is registered. This preserves the ADR-160 safety gate.
+    pub fn new() -> Self {
+        let mut skills: Vec<Box<dyn EdgeSkill>> = Vec::new();
+        let mut medical_flags: Vec<bool> = Vec::new();
+
+        crate::skill_registry::register_default(&mut skills, &mut medical_flags);
+        #[cfg(feature = "medical-experimental")]
+        crate::skill_registry::register_medical(&mut skills, &mut medical_flags);
+
+        Self {
+            skills,
+            medical_flags,
+            frame_count: 0,
+        }
+    }
+
+    /// Number of registered skills (default tier, or +medical if that feature is on).
+    pub fn skill_count(&self) -> usize {
+        self.skills.len()
+    }
+
+    /// Run every registered skill over one frame, aggregating all emitted events
+    /// tagged by source skill. Order matches registration order.
+    pub fn on_frame(&mut self, frame: &CsiFrameView) -> Vec<SkillEvent> {
+        self.frame_count += 1;
+        let mut out: Vec<SkillEvent> = Vec::new();
+        for skill in self.skills.iter_mut() {
+            let name = skill.name();
+            for &(event_id, value) in skill.on_frame(frame) {
+                out.push(SkillEvent {
+                    skill: name,
+                    event_id,
+                    value,
+                });
+            }
+        }
+        out
+    }
+
+    /// Total frames processed so far.
+    pub fn frame_count(&self) -> u64 {
+        self.frame_count
+    }
+
+    /// Introspection: list every registered skill with its event ids and tier.
+    pub fn skills(&self) -> Vec<SkillInfo> {
+        let mut out = Vec::with_capacity(self.skills.len());
+        for (i, skill) in self.skills.iter().enumerate() {
+            out.push(SkillInfo {
+                name: skill.name(),
+                event_ids: skill.event_ids(),
+                medical_experimental: self.medical_flags.get(i).copied().unwrap_or(false),
+            });
+        }
+        out
+    }
+}
+
+impl Default for EdgePipeline {
+    fn default() -> Self {
+        Self::new()
+    }
+}
@@ -0,0 +1,630 @@
+//! Adapters wiring every runtime skill detector to the uniform [`EdgeSkill`]
+//! trait, plus the registration functions consumed by [`EdgePipeline::new`].
+//!
+//! [`EdgePipeline::new`]: crate::pipeline_all::EdgePipeline::new
+//! [`EdgeSkill`]: crate::pipeline_all::EdgeSkill
+//!
+//! # How adapters work
+//!
+//! Each underlying detector keeps its own bespoke `process_frame`/`on_timer`
+//! signature and its owned `events: [(i32,f32); N]` buffer (the ADR-160 M6
+//! soundness fix). An adapter holds the detector, implements [`EdgeSkill`], and
+//! in `on_frame` simply pulls the needed fields out of [`CsiFrameView`] and
+//! forwards the call **unchanged**. The detector returns `&self.events[..n]`;
+//! the adapter forwards that borrow directly, so no extra buffer or copy is
+//! needed for the common case.
+//!
+//! Three families need a small owned scratch buffer in the adapter instead of a
+//! direct forward, because the underlying entry point does not itself return a
+//! `&[(i32,f32)]`:
+//! - `gesture` (`-> Option<u8>`), `coherence` (`-> f32`), `adversarial`
+//!   (`-> bool`): the adapter synthesizes a single tagged event.
+//! - `sig_sparse_recovery` (`process_frame(&mut [f32])`): the adapter copies the
+//!   frame amplitudes into an owned scratch slice so the in-place ISTA recovery
+//!   never mutates the shared frame, then forwards the borrow.
+//! - timer-driven skills (`vital_trend`, `lrn_meta_adapt`, `sig_temporal_compress`,
+//!   `tmp_goap_autonomy`, `tmp_pattern_sequence`): their `on_timer()` is driven
+//!   once per frame here (a frame *is* the tick at the edge), forwarding the
+//!   borrow. `tmp_pattern_sequence` additionally calls its `on_frame(...)`
+//!   accumulator first.
+//!
+//! **No skill's DSP is changed.** Only the call wiring lives here.
+
+#![cfg(feature = "std")]
+
+extern crate std;
+use std::boxed::Box;
+use std::vec::Vec;
+
+use crate::pipeline_all::{CsiFrameView, EdgeSkill};
+
+// ── Direct-forward adapter macro ─────────────────────────────────────────────
+//
+// Generates an adapter whose `on_frame` forwards directly to a detector method
+// that already returns `&[(i32, f32)]`. `$call` is an expression over `self.0`
+// (the detector) and `f` (the `&CsiFrameView`).
+macro_rules! fwd_skill {
+    ($adapter:ident, $detector:path, $name:literal, $ids:expr, |$d:ident, $f:ident| $call:expr) => {
+        pub struct $adapter($detector);
+        impl $adapter {
+            pub fn new() -> Self {
+                Self(<$detector>::new())
+            }
+        }
+        impl EdgeSkill for $adapter {
+            fn name(&self) -> &'static str {
+                $name
+            }
+            fn event_ids(&self) -> &'static [i32] {
+                &$ids
+            }
+            fn on_frame(&mut self, $f: &CsiFrameView) -> &[(i32, f32)] {
+                let $d = &mut self.0;
+                $call
+            }
+        }
+    };
+}
+
+// ── Synthesized-event adapter macro ──────────────────────────────────────────
+//
+// For detectors whose entry point does NOT return `&[(i32, f32)]`. The adapter
+// owns a tiny scratch buffer; `$body` (over `self`, `f`, and `self.buf`/`self.n`)
+// fills it and the trait returns the filled prefix.
+macro_rules! synth_skill {
+    ($adapter:ident, $detector:path, $name:literal, $ids:expr, $buf:literal,
+     |$s:ident, $f:ident| $body:block) => {
+        pub struct $adapter {
+            det: $detector,
+            buf: [(i32, f32); $buf],
+            n: usize,
+        }
+        impl $adapter {
+            pub fn new() -> Self {
+                Self {
+                    det: <$detector>::new(),
+                    buf: [(0, 0.0); $buf],
+                    n: 0,
+                }
+            }
+        }
+        impl EdgeSkill for $adapter {
+            fn name(&self) -> &'static str {
+                $name
+            }
+            fn event_ids(&self) -> &'static [i32] {
+                &$ids
+            }
+            fn on_frame(&mut self, $f: &CsiFrameView) -> &[(i32, f32)] {
+                let $s = self;
+                $s.n = 0;
+                $body
+                &$s.buf[..$s.n]
+            }
+        }
+    };
+}
+
+use crate::event_types as ev;
+
+// ── Flagship (synthesized) ───────────────────────────────────────────────────
+
+synth_skill!(GestureAdapter, crate::gesture::GestureDetector, "gesture",
+    [ev::GESTURE_DETECTED], 1, |s, f| {
+        if let Some(id) = s.det.process_frame(f.phases) {
+            s.buf[0] = (ev::GESTURE_DETECTED, id as f32);
+            s.n = 1;
+        }
+    });
+
+synth_skill!(CoherenceAdapter, crate::coherence::CoherenceMonitor, "coherence",
+    [ev::COHERENCE_SCORE], 1, |s, f| {
+        let score = s.det.process_frame(f.phases);
+        s.buf[0] = (ev::COHERENCE_SCORE, score);
+        s.n = 1;
+    });
+
+synth_skill!(AdversarialAdapter, crate::adversarial::AnomalyDetector, "adversarial",
+    [ev::ANOMALY_DETECTED], 1, |s, f| {
+        if s.det.process_frame(f.phases, f.amplitudes) {
+            s.buf[0] = (ev::ANOMALY_DETECTED, 1.0);
+            s.n = 1;
+        }
+    });
+
+// ── sig_sparse_recovery (needs owned mutable amplitude scratch) ───────────────
+
+const SPARSE_SC: usize = 64;
+pub struct SparseRecoveryAdapter {
+    det: crate::sig_sparse_recovery::SparseRecovery,
+    scratch: [f32; SPARSE_SC],
+}
+impl SparseRecoveryAdapter {
+    pub fn new() -> Self {
+        Self {
+            det: crate::sig_sparse_recovery::SparseRecovery::new(),
+            scratch: [0.0; SPARSE_SC],
+        }
+    }
+}
+impl EdgeSkill for SparseRecoveryAdapter {
+    fn name(&self) -> &'static str {
+        "sig_sparse_recovery"
+    }
+    fn event_ids(&self) -> &'static [i32] {
+        &[ev::RECOVERY_COMPLETE, ev::RECOVERY_ERROR, ev::DROPOUT_RATE]
+    }
+    fn on_frame(&mut self, f: &CsiFrameView) -> &[(i32, f32)] {
+        let n = f.amplitudes.len().min(SPARSE_SC);
+        self.scratch[..n].copy_from_slice(&f.amplitudes[..n]);
+        self.det.process_frame(&mut self.scratch[..n])
+    }
+}
+
+// ── Standard direct-forward skills (return &[(i32,f32)]) ─────────────────────
+
+fwd_skill!(AisBehavioralAdapter, crate::ais_behavioral_profiler::BehavioralProfiler,
+    "ais_behavioral_profiler",
+    [ev::BEHAVIOR_ANOMALY, ev::PROFILE_DEVIATION, ev::NOVEL_PATTERN, ev::PROFILE_MATURITY],
+    |d, f| d.process_frame(f.presence != 0, f.motion_energy, f.n_persons.max(0) as u8));
+
+fwd_skill!(AisPromptShieldAdapter, crate::ais_prompt_shield::PromptShield,
+    "ais_prompt_shield",
+    [ev::REPLAY_ATTACK, ev::INJECTION_DETECTED, ev::JAMMING_DETECTED, ev::SIGNAL_INTEGRITY],
+    |d, f| d.process_frame(f.phases, f.amplitudes));
+
+fwd_skill!(AutPsychoAdapter, crate::aut_psycho_symbolic::PsychoSymbolicEngine,
+    "aut_psycho_symbolic",
+    [ev::INFERENCE_RESULT, ev::INFERENCE_CONFIDENCE, ev::RULE_FIRED, ev::CONTRADICTION],
+    |d, f| d.process_frame(f.presence as f32, f.motion_energy, f.breathing_bpm,
+        f.heartrate_bpm, f.n_persons as f32, 0.0));
+
+fwd_skill!(AutMeshAdapter, crate::aut_self_healing_mesh::SelfHealingMesh,
+    "aut_self_healing_mesh",
+    [ev::NODE_DEGRADED, ev::MESH_RECONFIGURE, ev::COVERAGE_SCORE, ev::HEALING_COMPLETE],
+    |d, f| d.process_frame(f.variances));
+
+fwd_skill!(BldElevatorAdapter, crate::bld_elevator_count::ElevatorCounter,
+    "bld_elevator_count",
+    [ev::ELEVATOR_COUNT, ev::DOOR_OPEN, ev::DOOR_CLOSE, ev::OVERLOAD_WARNING],
+    |d, f| d.process_frame(f.amplitudes, f.phases, f.motion_energy, f.n_persons));
+
+fwd_skill!(BldEnergyAdapter, crate::bld_energy_audit::EnergyAuditor,
+    "bld_energy_audit",
+    [ev::SCHEDULE_SUMMARY, ev::AFTER_HOURS_ALERT, ev::UTILIZATION_RATE],
+    |d, f| d.process_frame(f.presence, f.n_persons));
+
+fwd_skill!(BldHvacAdapter, crate::bld_hvac_presence::HvacPresenceDetector,
+    "bld_hvac_presence",
+    [ev::HVAC_OCCUPIED, ev::ACTIVITY_LEVEL, ev::DEPARTURE_COUNTDOWN],
+    |d, f| d.process_frame(f.presence as f32, f.motion_energy));
+
+fwd_skill!(BldLightingAdapter, crate::bld_lighting_zones::LightingZoneController,
+    "bld_lighting_zones",
+    [ev::LIGHT_ON, ev::LIGHT_DIM, ev::LIGHT_OFF],
+    |d, f| d.process_frame(f.amplitudes, f.motion_energy));
+
+fwd_skill!(BldMeetingAdapter, crate::bld_meeting_room::MeetingRoomTracker,
+    "bld_meeting_room",
+    [ev::MEETING_START, ev::MEETING_END, ev::PEAK_HEADCOUNT, ev::ROOM_AVAILABLE],
+    |d, f| d.process_frame(f.presence, f.n_persons, f.motion_energy));
+
+fwd_skill!(ExoBreathingSyncAdapter, crate::exo_breathing_sync::BreathingSyncDetector,
+    "exo_breathing_sync",
+    [ev::SYNC_DETECTED, ev::SYNC_PAIR_COUNT, ev::GROUP_COHERENCE, ev::SYNC_LOST],
+    |d, f| d.process_frame(f.phases, f.variances, f.breathing_bpm, f.n_persons));
+
+fwd_skill!(ExoEmotionAdapter, crate::exo_emotion_detect::EmotionDetector,
+    "exo_emotion_detect",
+    [ev::AROUSAL_LEVEL, ev::STRESS_INDEX, ev::CALM_DETECTED, ev::AGITATION_DETECTED],
+    |d, f| d.process_frame(f.breathing_bpm, f.heartrate_bpm, f.motion_energy,
+        f.phase_mean(), f.variance_mean));
+
+fwd_skill!(ExoDreamAdapter, crate::exo_dream_stage::DreamStageDetector,
+    "exo_dream_stage",
+    [ev::SLEEP_STAGE, ev::SLEEP_QUALITY, ev::REM_EPISODE, ev::DEEP_SLEEP_RATIO],
+    |d, f| d.process_frame(f.breathing_bpm, f.heartrate_bpm, f.motion_energy,
+        f.phase_mean(), f.variance_mean, f.presence));
+
+fwd_skill!(ExoGestureLangAdapter, crate::exo_gesture_language::GestureLanguageDetector,
+    "exo_gesture_language",
+    [ev::LETTER_RECOGNIZED, ev::LETTER_CONFIDENCE, ev::WORD_BOUNDARY, ev::GESTURE_REJECTED],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.variance_mean, f.motion_energy, f.presence));
+
+fwd_skill!(ExoGhostAdapter, crate::exo_ghost_hunter::GhostHunterDetector,
+    "exo_ghost_hunter",
+    [ev::EXO_ANOMALY_DETECTED, ev::EXO_ANOMALY_CLASS, ev::HIDDEN_PRESENCE, ev::ENVIRONMENTAL_DRIFT],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.variances, f.presence, f.motion_energy));
+
+fwd_skill!(ExoHappinessAdapter, crate::exo_happiness_score::HappinessScoreDetector,
+    "exo_happiness_score",
+    [ev::HAPPINESS_SCORE, ev::GAIT_ENERGY, ev::AFFECT_VALENCE, ev::SOCIAL_ENERGY, ev::TRANSIT_DIRECTION],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.variances, f.presence,
+        f.motion_energy, f.breathing_bpm, f.heartrate_bpm));
+
+fwd_skill!(ExoHyperbolicAdapter, crate::exo_hyperbolic_space::HyperbolicEmbedder,
+    "exo_hyperbolic_space",
+    [ev::HIERARCHY_LEVEL, ev::HYPERBOLIC_RADIUS, ev::LOCATION_LABEL],
+    |d, f| d.process_frame(f.amplitudes));
+
+fwd_skill!(ExoMusicAdapter, crate::exo_music_conductor::MusicConductorDetector,
+    "exo_music_conductor",
+    [ev::CONDUCTOR_BPM, ev::BEAT_POSITION, ev::DYNAMIC_LEVEL, ev::GESTURE_CUTOFF, ev::GESTURE_FERMATA],
+    |d, f| d.process_frame(f.phase_mean(), f.amplitude_mean(), f.motion_energy, f.variance_mean));
+
+fwd_skill!(ExoPlantAdapter, crate::exo_plant_growth::PlantGrowthDetector,
+    "exo_plant_growth",
+    [ev::GROWTH_RATE, ev::CIRCADIAN_PHASE, ev::WILT_DETECTED, ev::WATERING_EVENT],
+    |d, f| d.process_frame(f.amplitudes, f.phases, f.variances, f.presence));
+
+fwd_skill!(ExoRainAdapter, crate::exo_rain_detect::RainDetector,
+    "exo_rain_detect",
+    [ev::RAIN_ONSET, ev::RAIN_INTENSITY, ev::RAIN_CESSATION],
+    |d, f| d.process_frame(f.phases, f.variances, f.amplitudes, f.presence));
+
+fwd_skill!(ExoTimeCrystalAdapter, crate::exo_time_crystal::TimeCrystalDetector,
+    "exo_time_crystal",
+    [ev::CRYSTAL_DETECTED, ev::CRYSTAL_STABILITY, ev::COORDINATION_INDEX],
+    |d, f| d.process_frame(f.motion_energy));
+
+fwd_skill!(IndCleanRoomAdapter, crate::ind_clean_room::CleanRoomMonitor,
+    "ind_clean_room",
+    [ev::OCCUPANCY_COUNT, ev::OCCUPANCY_VIOLATION, ev::TURBULENT_MOTION, ev::COMPLIANCE_REPORT],
+    |d, f| d.process_frame(f.n_persons, f.presence, f.motion_energy));
+
+fwd_skill!(IndConfinedAdapter, crate::ind_confined_space::ConfinedSpaceMonitor,
+    "ind_confined_space",
+    [ev::WORKER_ENTRY, ev::WORKER_EXIT, ev::BREATHING_OK, ev::EXTRACTION_ALERT, ev::IMMOBILE_ALERT],
+    |d, f| d.process_frame(f.presence, f.breathing_bpm, f.motion_energy, f.variance_mean));
+
+fwd_skill!(IndForkliftAdapter, crate::ind_forklift_proximity::ForkliftProximityDetector,
+    "ind_forklift_proximity",
+    [ev::PROXIMITY_WARNING, ev::VEHICLE_DETECTED, ev::HUMAN_NEAR_VEHICLE],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.variances, f.motion_energy, f.presence, f.n_persons));
+
+fwd_skill!(IndLivestockAdapter, crate::ind_livestock_monitor::LivestockMonitor,
+    "ind_livestock_monitor",
+    [ev::ANIMAL_PRESENT, ev::ABNORMAL_STILLNESS, ev::LABORED_BREATHING, ev::ESCAPE_ALERT],
+    |d, f| d.process_frame(f.presence, f.breathing_bpm, f.motion_energy, f.variance_mean));
+
+fwd_skill!(IndVibrationAdapter, crate::ind_structural_vibration::StructuralVibrationMonitor,
+    "ind_structural_vibration",
+    [ev::SEISMIC_DETECTED, ev::MECHANICAL_RESONANCE, ev::STRUCTURAL_DRIFT, ev::VIBRATION_SPECTRUM],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.variances, f.presence));
+
+fwd_skill!(IntrusionAdapter, crate::intrusion::IntrusionDetector,
+    "intrusion",
+    [ev::INTRUSION_ALERT, ev::INTRUSION_ZONE, 202],
+    |d, f| d.process_frame(f.phases, f.amplitudes));
+
+fwd_skill!(LrnAttractorAdapter, crate::lrn_anomaly_attractor::AttractorDetector,
+    "lrn_anomaly_attractor",
+    [ev::ATTRACTOR_TYPE, ev::LYAPUNOV_EXPONENT, ev::BASIN_DEPARTURE, ev::LEARNING_COMPLETE],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.motion_energy));
+
+fwd_skill!(LrnDtwAdapter, crate::lrn_dtw_gesture_learn::GestureLearner,
+    "lrn_dtw_gesture_learn",
+    [ev::GESTURE_LEARNED, ev::GESTURE_MATCHED, ev::LRN_MATCH_DISTANCE, ev::TEMPLATE_COUNT],
+    |d, f| d.process_frame(f.phases, f.motion_energy));
+
+fwd_skill!(LrnEwcAdapter, crate::lrn_ewc_lifelong::EwcLifelong,
+    "lrn_ewc_lifelong",
+    [ev::KNOWLEDGE_RETAINED, ev::NEW_TASK_LEARNED, ev::FISHER_UPDATE, ev::FORGETTING_RISK],
+    |d, f| d.process_frame(f.variances, f.presence));
+
+fwd_skill!(OccupancyAdapter, crate::occupancy::OccupancyDetector,
+    "occupancy",
+    [ev::ZONE_OCCUPIED, ev::ZONE_COUNT, ev::ZONE_TRANSITION],
+    |d, f| d.process_frame(f.phases, f.amplitudes));
+
+fwd_skill!(QntInterferenceAdapter, crate::qnt_interference_search::InterferenceSearch,
+    "qnt_interference_search",
+    [ev::HYPOTHESIS_WINNER, ev::HYPOTHESIS_AMPLITUDE, ev::SEARCH_ITERATIONS],
+    |d, f| d.process_frame(f.presence, f.motion_energy, f.n_persons));
+
+fwd_skill!(QntCoherenceAdapter, crate::qnt_quantum_coherence::QuantumCoherenceMonitor,
+    "qnt_quantum_coherence",
+    [ev::ENTANGLEMENT_ENTROPY, ev::DECOHERENCE_EVENT, ev::BLOCH_DRIFT],
+    |d, f| d.process_frame(f.phases));
+
+fwd_skill!(RetFlowAdapter, crate::ret_customer_flow::CustomerFlowTracker,
+    "ret_customer_flow",
+    [ev::INGRESS, ev::EGRESS, ev::NET_OCCUPANCY, ev::HOURLY_TRAFFIC],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.variance_mean, f.motion_energy));
+
+fwd_skill!(RetDwellAdapter, crate::ret_dwell_heatmap::DwellHeatmapTracker,
+    "ret_dwell_heatmap",
+    [ev::DWELL_ZONE_UPDATE, ev::HOT_ZONE, ev::COLD_ZONE, ev::SESSION_SUMMARY],
+    |d, f| d.process_frame(f.presence, f.variances, f.motion_energy, f.n_persons));
+
+fwd_skill!(RetQueueAdapter, crate::ret_queue_length::QueueLengthEstimator,
+    "ret_queue_length",
+    [ev::QUEUE_LENGTH, ev::WAIT_TIME_ESTIMATE, ev::SERVICE_RATE, ev::QUEUE_ALERT],
+    |d, f| d.process_frame(f.presence, f.n_persons, f.variance_mean, f.motion_energy));
+
+fwd_skill!(RetShelfAdapter, crate::ret_shelf_engagement::ShelfEngagementDetector,
+    "ret_shelf_engagement",
+    [ev::SHELF_BROWSE, ev::SHELF_CONSIDER, ev::SHELF_ENGAGE, ev::REACH_DETECTED],
+    |d, f| d.process_frame(f.presence, f.motion_energy, f.variance_mean, f.phases));
+
+fwd_skill!(RetTableAdapter, crate::ret_table_turnover::TableTurnoverTracker,
+    "ret_table_turnover",
+    [ev::TABLE_SEATED, ev::TABLE_VACATED, ev::TABLE_AVAILABLE, ev::TURNOVER_RATE],
+    |d, f| d.process_frame(f.presence, f.motion_energy, f.n_persons));
+
+fwd_skill!(SecLoiteringAdapter, crate::sec_loitering::LoiteringDetector,
+    "sec_loitering",
+    [ev::LOITERING_START, ev::LOITERING_ONGOING, ev::LOITERING_END],
+    |d, f| d.process_frame(f.presence, f.motion_energy));
+
+fwd_skill!(SecPanicAdapter, crate::sec_panic_motion::PanicMotionDetector,
+    "sec_panic_motion",
+    [ev::PANIC_DETECTED, ev::STRUGGLE_PATTERN, ev::FLEEING_DETECTED],
+    |d, f| d.process_frame(f.motion_energy, f.variance_mean, f.phase_mean(), f.presence));
+
+fwd_skill!(SecPerimeterAdapter, crate::sec_perimeter_breach::PerimeterBreachDetector,
+    "sec_perimeter_breach",
+    [ev::PERIMETER_BREACH, ev::APPROACH_DETECTED, ev::DEPARTURE_DETECTED, ev::SEC_ZONE_TRANSITION],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.variances, f.motion_energy));
+
+fwd_skill!(SecTailgateAdapter, crate::sec_tailgating::TailgateDetector,
+    "sec_tailgating",
+    [ev::TAILGATE_DETECTED, ev::SINGLE_PASSAGE, ev::MULTI_PASSAGE],
+    |d, f| d.process_frame(f.motion_energy, f.presence, f.n_persons, f.variance_mean));
+
+fwd_skill!(SecWeaponAdapter, crate::sec_weapon_detect::WeaponDetector,
+    "sec_weapon_detect",
+    [ev::METAL_ANOMALY, ev::HIGH_METAL_REFLECTIVITY, ev::CALIBRATION_NEEDED],
+    |d, f| d.process_frame(f.phases, f.amplitudes, f.variances, f.motion_energy, f.presence));
+
+fwd_skill!(SigCoherenceGateAdapter, crate::sig_coherence_gate::CoherenceGate,
+    "sig_coherence_gate",
+    [ev::GATE_DECISION, ev::SIG_COHERENCE_SCORE, ev::RECALIBRATE_NEEDED],
+    |d, f| d.process_frame(f.phases));
+
+fwd_skill!(SigFlashAttnAdapter, crate::sig_flash_attention::FlashAttention,
+    "sig_flash_attention",
+    [ev::ATTENTION_PEAK_SC, ev::ATTENTION_SPREAD, ev::SPATIAL_FOCUS_ZONE],
+    |d, f| d.process_frame(f.phases, f.amplitudes));
+
+fwd_skill!(SigMincutAdapter, crate::sig_mincut_person_match::PersonMatcher,
+    "sig_mincut_person_match",
+    [ev::PERSON_ID_ASSIGNED, ev::PERSON_ID_SWAP, ev::MATCH_CONFIDENCE],
+    |d, f| d.process_frame(f.amplitudes, f.variances, f.n_persons.max(0) as usize));
+
+fwd_skill!(SigTransportAdapter, crate::sig_optimal_transport::OptimalTransportDetector,
+    "sig_optimal_transport",
+    [ev::WASSERSTEIN_DISTANCE, ev::DISTRIBUTION_SHIFT, ev::SUBTLE_MOTION],
+    |d, f| d.process_frame(f.amplitudes));
+
+fwd_skill!(SptHnswAdapter, crate::spt_micro_hnsw::MicroHnsw,
+    "spt_micro_hnsw",
+    [ev::NEAREST_MATCH_ID, ev::HNSW_MATCH_DISTANCE, ev::CLASSIFICATION, ev::LIBRARY_SIZE],
+    |d, f| d.process_frame(f.variances));
+
+fwd_skill!(SptPagerankAdapter, crate::spt_pagerank_influence::PageRankInfluence,
+    "spt_pagerank_influence",
+    [ev::DOMINANT_PERSON, ev::INFLUENCE_SCORE, ev::INFLUENCE_CHANGE],
+    |d, f| d.process_frame(f.phases, f.n_persons.max(0) as usize));
+
+fwd_skill!(SptSpikingAdapter, crate::spt_spiking_tracker::SpikingTracker,
+    "spt_spiking_tracker",
+    [ev::TRACK_UPDATE, ev::TRACK_VELOCITY, ev::SPIKE_RATE, ev::TRACK_LOST],
+    |d, f| d.process_frame(f.phases, f.prev_phases));
+
+fwd_skill!(TmpLogicGuardAdapter, crate::tmp_temporal_logic_guard::TemporalLogicGuard,
+    "tmp_temporal_logic_guard",
+    [ev::LTL_VIOLATION, ev::LTL_SATISFACTION, ev::COUNTEREXAMPLE],
+    |d, f| {
+        let input = crate::tmp_temporal_logic_guard::FrameInput {
+            presence: f.presence,
+            n_persons: f.n_persons,
+            motion_energy: f.motion_energy,
+            coherence: f.coherence,
+            breathing_bpm: f.breathing_bpm,
+            heartrate_bpm: f.heartrate_bpm,
+            fall_alert: false,
+            intrusion_alert: false,
+            person_id_active: f.n_persons > 0,
+            vital_signs_active: f.breathing_bpm > 0.0,
+            seizure_detected: false,
+            normal_gait: true,
+        };
+        d.on_frame(&input)
+    });
+
+// ── Timer-driven skills (driven once per frame) ──────────────────────────────
+
+fwd_skill!(VitalTrendAdapter, crate::vital_trend::VitalTrendAnalyzer,
+    "vital_trend",
+    // 101-105 = brady/tachypnea, brady/tachycardia, apnea; 110/111 = breathing/heartrate
+    // moving averages (module-local EVENT_BREATHING_AVG / EVENT_HEARTRATE_AVG).
+    [ev::BRADYPNEA, ev::TACHYPNEA, ev::BRADYCARDIA, ev::TACHYCARDIA, ev::APNEA, 110, 111],
+    |d, f| d.on_timer(f.breathing_bpm, f.heartrate_bpm));
+
+fwd_skill!(LrnMetaAdapter, crate::lrn_meta_adapt::MetaAdapter,
+    "lrn_meta_adapt",
+    [ev::PARAM_ADJUSTED, ev::ADAPTATION_SCORE, ev::ROLLBACK_TRIGGERED, ev::META_LEVEL],
+    |d, _f| d.on_timer());
+
+fwd_skill!(SigTemporalCompressAdapter, crate::sig_temporal_compress::TemporalCompressor,
+    "sig_temporal_compress",
+    [ev::COMPRESSION_RATIO, ev::TIER_TRANSITION, ev::HISTORY_DEPTH_HOURS],
+    |d, _f| d.on_timer());
+
+fwd_skill!(TmpGoapAdapter, crate::tmp_goap_autonomy::GoapPlanner,
+    "tmp_goap_autonomy",
+    [ev::GOAL_SELECTED, ev::MODULE_ACTIVATED, ev::MODULE_DEACTIVATED, ev::PLAN_COST],
+    |d, _f| d.on_timer());
+
+// tmp_pattern_sequence: accumulate via on_frame, then drive on_timer per frame.
+pub struct TmpPatternAdapter(crate::tmp_pattern_sequence::PatternSequenceAnalyzer);
+impl TmpPatternAdapter {
+    pub fn new() -> Self {
+        Self(crate::tmp_pattern_sequence::PatternSequenceAnalyzer::new())
+    }
+}
+impl EdgeSkill for TmpPatternAdapter {
+    fn name(&self) -> &'static str {
+        "tmp_pattern_sequence"
+    }
+    fn event_ids(&self) -> &'static [i32] {
+        &[ev::PATTERN_DETECTED, ev::PATTERN_CONFIDENCE, ev::ROUTINE_DEVIATION, ev::PREDICTION_NEXT]
+    }
+    fn on_frame(&mut self, f: &CsiFrameView) -> &[(i32, f32)] {
+        self.0.on_frame(f.presence, f.motion_energy, f.n_persons);
+        self.0.on_timer()
+    }
+}
+
+// ── Medical tier (gated) ─────────────────────────────────────────────────────
+
+#[cfg(feature = "medical-experimental")]
+mod medical {
+    use super::*;
+
+    // Medical event ids verified against each module's local consts (100-199 block).
+    fwd_skill!(MedCardiacAdapter, crate::med_cardiac_arrhythmia::CardiacArrhythmiaDetector,
+        "med_cardiac_arrhythmia",
+        [110, 111, 112, 113],
+        |d, f| d.process_frame(f.heartrate_bpm, f.phase_mean()));
+
+    fwd_skill!(MedGaitAdapter, crate::med_gait_analysis::GaitAnalyzer,
+        "med_gait_analysis",
+        [130, 131, 132, 133, 134],
+        |d, f| d.process_frame(f.phase_mean(), f.amplitude_mean(), f.variance_mean, f.motion_energy));
+
+    fwd_skill!(MedRespiratoryAdapter, crate::med_respiratory_distress::RespiratoryDistressDetector,
+        "med_respiratory_distress",
+        [120, 121, 122, 123],
+        |d, f| d.process_frame(f.breathing_bpm, f.phase_mean(), f.variance_mean));
+
+    fwd_skill!(MedSeizureAdapter, crate::med_seizure_detect::SeizureDetector,
+        "med_seizure_detect",
+        [140, 141, 142, 143],
+        |d, f| d.process_frame(f.phase_mean(), f.amplitude_mean(), f.motion_energy, f.presence));
+
+    fwd_skill!(MedApneaAdapter, crate::med_sleep_apnea::SleepApneaDetector,
+        "med_sleep_apnea",
+        [100, 101, 102],
+        |d, f| d.process_frame(f.breathing_bpm, f.presence, f.variance_mean));
+
+    pub fn register(skills: &mut Vec<Box<dyn EdgeSkill>>, med: &mut Vec<bool>) {
+        macro_rules! push {
+            ($a:ty) => {{
+                skills.push(Box::new(<$a>::new()));
+                med.push(true);
+            }};
+        }
+        push!(MedSeizureAdapter);
+        push!(MedCardiacAdapter);
+        push!(MedRespiratoryAdapter);
+        push!(MedApneaAdapter);
+        push!(MedGaitAdapter);
+    }
+}
+
+// ── Registration ─────────────────────────────────────────────────────────────
+
+/// Register every default-tier (non-medical) skill.
+pub fn register_default(skills: &mut Vec<Box<dyn EdgeSkill>>, med: &mut Vec<bool>) {
+    macro_rules! push {
+        ($a:ty) => {{
+            skills.push(Box::new(<$a>::new()));
+            med.push(false);
+        }};
+    }
+
+    // Flagship + synthesized
+    push!(GestureAdapter);
+    push!(CoherenceAdapter);
+    push!(AdversarialAdapter);
+    push!(OccupancyAdapter);
+    push!(IntrusionAdapter);
+    push!(VitalTrendAdapter);
+
+    // Security
+    push!(SecPerimeterAdapter);
+    push!(SecWeaponAdapter);
+    push!(SecTailgateAdapter);
+    push!(SecLoiteringAdapter);
+    push!(SecPanicAdapter);
+
+    // Smart building
+    push!(BldHvacAdapter);
+    push!(BldLightingAdapter);
+    push!(BldElevatorAdapter);
+    push!(BldMeetingAdapter);
+    push!(BldEnergyAdapter);
+
+    // Retail
+    push!(RetQueueAdapter);
+    push!(RetDwellAdapter);
+    push!(RetFlowAdapter);
+    push!(RetTableAdapter);
+    push!(RetShelfAdapter);
+
+    // Industrial
+    push!(IndForkliftAdapter);
+    push!(IndConfinedAdapter);
+    push!(IndCleanRoomAdapter);
+    push!(IndLivestockAdapter);
+    push!(IndVibrationAdapter);
+
+    // Exotic / research
+    push!(ExoTimeCrystalAdapter);
+    push!(ExoHyperbolicAdapter);
+    push!(ExoDreamAdapter);
+    push!(ExoEmotionAdapter);
+    push!(ExoGestureLangAdapter);
+    push!(ExoMusicAdapter);
+    push!(ExoPlantAdapter);
+    push!(ExoGhostAdapter);
+    push!(ExoRainAdapter);
+    push!(ExoBreathingSyncAdapter);
+    push!(ExoHappinessAdapter);
+
+    // Signal intelligence
+    push!(SigCoherenceGateAdapter);
+    push!(SigFlashAttnAdapter);
+    push!(SigTemporalCompressAdapter);
+    push!(SparseRecoveryAdapter);
+    push!(SigMincutAdapter);
+    push!(SigTransportAdapter);
+
+    // Adaptive learning
+    push!(LrnDtwAdapter);
+    push!(LrnAttractorAdapter);
+    push!(LrnMetaAdapter);
+    push!(LrnEwcAdapter);
+
+    // Spatial reasoning
+    push!(SptPagerankAdapter);
+    push!(SptHnswAdapter);
+    push!(SptSpikingAdapter);
+
+    // Temporal analysis
+    push!(TmpPatternAdapter);
+    push!(TmpLogicGuardAdapter);
+    push!(TmpGoapAdapter);
+
+    // AI security
+    push!(AisPromptShieldAdapter);
+    push!(AisBehavioralAdapter);
+
+    // Quantum-inspired
+    push!(QntCoherenceAdapter);
+    push!(QntInterferenceAdapter);
+
+    // Autonomous systems
+    push!(AutPsychoAdapter);
+    push!(AutMeshAdapter);
+
+    let _ = (skills.len(), med.len());
+}
+
+/// Register the gated `medical-experimental` tier (5 `med_*` skills).
+#[cfg(feature = "medical-experimental")]
+pub fn register_medical(skills: &mut Vec<Box<dyn EdgeSkill>>, med: &mut Vec<bool>) {
+    medical::register(skills, med);
+}
@@ -0,0 +1,208 @@
+//! Integration test for the unified [`EdgePipeline`] (ADR-160 deliverable 1).
+//!
+//! Proves that EVERY registered skill executes over a deterministic synthetic
+//! CSI frame sequence without panicking, that the aggregated event stream is
+//! well-formed (each event tagged with a known skill name + a declared event
+//! id), and pins the registered-skill count (default vs +medical-experimental).
+//!
+//! Run:
+//!   cargo test --features std --test pipeline_all
+//!   cargo test --features std,medical-experimental --test pipeline_all
+//!
+//! [`EdgePipeline`]: wifi_densepose_wasm_edge::pipeline_all::EdgePipeline
+
+#![cfg(feature = "std")]
+
+use wifi_densepose_wasm_edge::pipeline_all::{CsiFrameView, EdgePipeline};
+
+const N_SC: usize = 32;
+
+/// Deterministic synthetic frame: a moving breathing/heartbeat target plus
+/// structured per-subcarrier phase/amplitude. No randomness — fully reproducible.
+fn synth_frame(t: usize, phases: &mut [f32], amps: &mut [f32], vars: &mut [f32]) {
+    let tf = t as f32;
+    // 0.3 Hz breathing modulation @ 20 Hz frame rate -> period ~66 frames.
+    let breath = (tf * 2.0 * core::f32::consts::PI * 0.3 / 20.0).sin();
+    // 1.2 Hz heartbeat.
+    let heart = (tf * 2.0 * core::f32::consts::PI * 1.2 / 20.0).sin();
+    for i in 0..phases.len() {
+        let sc = i as f32;
+        phases[i] = (sc * 0.21 + tf * 0.05).sin() + 0.15 * breath;
+        amps[i] = 1.0 + 0.3 * (sc * 0.11 + tf * 0.03).cos() + 0.1 * heart;
+        // motion-correlated variance, with one occasionally-hot zone.
+        vars[i] = 0.02 + 0.01 * (sc * 0.3).sin().abs() + if (t / 40) % 2 == 0 { 0.05 } else { 0.0 };
+    }
+}
+
+/// Build a view over the supplied buffers for frame `t`.
+fn view<'a>(
+    t: usize,
+    phases: &'a [f32],
+    amps: &'a [f32],
+    vars: &'a [f32],
+    prev_phases: &'a [f32],
+) -> CsiFrameView<'a> {
+    let tf = t as f32;
+    let motion = 0.3 + 0.2 * (tf * 0.07).sin().abs();
+    let mut vmean = 0.0f32;
+    for &v in vars {
+        vmean += v;
+    }
+    vmean /= vars.len().max(1) as f32;
+    CsiFrameView {
+        phases,
+        amplitudes: amps,
+        variances: vars,
+        prev_phases,
+        presence: if (t / 30) % 3 == 0 { 0 } else { 1 },
+        n_persons: ((t / 50) % 3) as i32,
+        motion_energy: motion,
+        breathing_bpm: 18.0 + 2.0 * (tf * 0.01).sin(),
+        heartrate_bpm: 72.0 + 5.0 * (tf * 0.02).sin(),
+        coherence: 0.5 + 0.4 * (tf * 0.03).cos(),
+        variance_mean: vmean,
+    }
+}
+
+#[test]
+fn all_skills_execute_without_panic_over_synthetic_stream() {
+    let mut pipeline = EdgePipeline::new();
+    let n_skills = pipeline.skill_count();
+    assert!(n_skills > 0, "pipeline must register skills");
+
+    let mut phases = [0.0f32; N_SC];
+    let mut amps = [0.0f32; N_SC];
+    let mut vars = [0.0f32; N_SC];
+    let mut prev_phases = [0.0f32; N_SC];
+
+    let known: std::collections::HashSet<&'static str> =
+        pipeline.skills().iter().map(|s| s.name).collect();
+
+    // Feed 300 frames (15 s @ 20 Hz) — enough for calibration windows, DTW
+    // enrollment, periodicity buffers, and timer cadences to fire.
+    let mut total_events = 0usize;
+    for t in 0..300 {
+        synth_frame(t, &mut phases, &mut amps, &mut vars);
+        let v = view(t, &phases, &amps, &vars, &prev_phases);
+        let events = pipeline.on_frame(&v);
+        for e in &events {
+            // Every event must be tagged with a registered skill name.
+            assert!(known.contains(e.skill), "unknown skill tag: {}", e.skill);
+            // Value must be finite (no NaN/Inf leaking from the DSP).
+            assert!(e.value.is_finite(), "non-finite value from {}", e.skill);
+        }
+        total_events += events.len();
+        prev_phases.copy_from_slice(&phases);
+    }
+
+    assert_eq!(pipeline.frame_count(), 300);
+    // A real run over 300 frames must emit *some* events across 59+ skills.
+    assert!(
+        total_events > 0,
+        "expected the skill library to emit events over 300 frames, got 0"
+    );
+    println!(
+        "pipeline: {} skills, {} aggregated events over 300 synthetic frames",
+        n_skills, total_events
+    );
+}
+
+#[test]
+fn every_emitted_event_id_is_declared_by_its_skill() {
+    // Stronger well-formedness: each event's id must be one the producing skill
+    // declared in its `event_ids()` introspection list.
+    let mut pipeline = EdgePipeline::new();
+
+    // skill name -> its declared event id set
+    let mut declared: std::collections::HashMap<&'static str, std::collections::HashSet<i32>> =
+        std::collections::HashMap::new();
+    for s in pipeline.skills() {
+        declared.insert(s.name, s.event_ids.iter().copied().collect());
+    }
+
+    let mut phases = [0.0f32; N_SC];
+    let mut amps = [0.0f32; N_SC];
+    let mut vars = [0.0f32; N_SC];
+    let mut prev_phases = [0.0f32; N_SC];
+
+    for t in 0..300 {
+        synth_frame(t, &mut phases, &mut amps, &mut vars);
+        let v = view(t, &phases, &amps, &vars, &prev_phases);
+        for e in &pipeline.on_frame(&v) {
+            let set = declared.get(e.skill).expect("skill declared");
+            assert!(
+                set.contains(&e.event_id),
+                "{} emitted undeclared event id {}",
+                e.skill,
+                e.event_id
+            );
+        }
+        prev_phases.copy_from_slice(&phases);
+    }
+}
+
+#[test]
+fn introspection_lists_every_skill_with_event_ids() {
+    let pipeline = EdgePipeline::new();
+    let infos = pipeline.skills();
+    assert_eq!(infos.len(), pipeline.skill_count());
+    for info in &infos {
+        assert!(!info.name.is_empty());
+        assert!(
+            !info.event_ids.is_empty(),
+            "skill {} declares no event ids",
+            info.name
+        );
+    }
+    // No duplicate skill names.
+    let names: std::collections::HashSet<_> = infos.iter().map(|i| i.name).collect();
+    assert_eq!(names.len(), infos.len(), "duplicate skill registration");
+}
+
+#[cfg(not(feature = "medical-experimental"))]
+#[test]
+fn default_tier_count_excludes_medical() {
+    let pipeline = EdgePipeline::new();
+    assert_eq!(
+        pipeline.skill_count(),
+        59,
+        "default (non-medical) tier must register exactly 59 skills"
+    );
+    // The ADR-160 safety gate: no med_* skill is present in the default build.
+    for info in pipeline.skills() {
+        assert!(
+            !info.medical_experimental,
+            "medical skill {} leaked into default tier",
+            info.name
+        );
+        assert!(
+            !info.name.starts_with("med_"),
+            "med_* skill {} present without the medical-experimental feature",
+            info.name
+        );
+    }
+}
+
+#[cfg(feature = "medical-experimental")]
+#[test]
+fn medical_tier_adds_five_skills() {
+    let pipeline = EdgePipeline::new();
+    assert_eq!(
+        pipeline.skill_count(),
+        64,
+        "default 59 + 5 medical = 64 skills"
+    );
+    let med: Vec<_> = pipeline
+        .skills()
+        .into_iter()
+        .filter(|s| s.medical_experimental)
+        .collect();
+    assert_eq!(med.len(), 5, "exactly 5 medical-experimental skills");
+    for m in &med {
+        assert!(
+            m.name.starts_with("med_"),
+            "medical-flagged skill has non-med_ name: {}",
+            m.name
+        );
+    }
+}
@@ -0,0 +1,762 @@
+//! Synthetic-ground-truth validation harness (ADR-160 deliverable 2).
+//!
+//! For the subset of edge skills whose detection target can be PLANTED with
+//! known ground truth, we generate N signals with known answers, run the real
+//! detector, and MEASURE detection rate / precision / recall / rate-error.
+//!
+//! # Honesty boundary
+//!
+//! This is **synthetic-ground-truth validation, NOT field accuracy.** A skill
+//! that recovers a planted sinusoid here is proven to do the math it claims on
+//! a constructed signal; it is NOT proven to work on real CSI in a real room.
+//!
+//! Skills whose detection target cannot be honestly planted on synthetic data
+//! (clinical seizure/apnea/arrhythmia/gait, weapon discrimination, affect/
+//! emotion/happiness, dream stage, sign language) are **NOT** validated here —
+//! see RESULTS.md "DATA-GATED" section. Planting a "seizure-like" wiggle and
+//! claiming the detector works validates nothing real.
+//!
+//! Run:
+//!   cargo test --features std --test synthetic_validation -- --nocapture
+//!
+//! The printed `MEASURED` lines are the source of `benchmarks/edge-skills/RESULTS.md`.
+
+#![cfg(feature = "std")]
+
+use std::f32::consts::PI;
+
+// ── Confusion-matrix accumulator ─────────────────────────────────────────────
+
+#[derive(Default, Clone, Copy)]
+struct Confusion {
+    tp: u32,
+    fp: u32,
+    tn: u32,
+    fn_: u32,
+}
+impl Confusion {
+    fn observe(&mut self, predicted_positive: bool, actual_positive: bool) {
+        match (predicted_positive, actual_positive) {
+            (true, true) => self.tp += 1,
+            (true, false) => self.fp += 1,
+            (false, false) => self.tn += 1,
+            (false, true) => self.fn_ += 1,
+        }
+    }
+    fn precision(&self) -> f32 {
+        let d = self.tp + self.fp;
+        if d == 0 {
+            1.0
+        } else {
+            self.tp as f32 / d as f32
+        }
+    }
+    fn recall(&self) -> f32 {
+        let d = self.tp + self.fn_;
+        if d == 0 {
+            1.0
+        } else {
+            self.tp as f32 / d as f32
+        }
+    }
+    fn accuracy(&self) -> f32 {
+        let d = self.tp + self.fp + self.tn + self.fn_;
+        if d == 0 {
+            0.0
+        } else {
+            (self.tp + self.tn) as f32 / d as f32
+        }
+    }
+    fn report(&self, name: &str) {
+        println!(
+            "MEASURED-on-synthetic | {:<34} | acc={:.3} prec={:.3} recall={:.3} | TP={} FP={} TN={} FN={}",
+            name,
+            self.accuracy(),
+            self.precision(),
+            self.recall(),
+            self.tp,
+            self.fp,
+            self.tn,
+            self.fn_
+        );
+    }
+}
+
+// ── 1. vital_trend — rate-threshold detection (directly verified thresholds) ─
+// Thresholds (from src/vital_trend.rs): BRADYPNEA<12, TACHYPNEA>25,
+// BRADYCARDIA<50, TACHYCARDIA>120, APNEA at breathing<1.0 for 20 calls;
+// ALERT_DEBOUNCE=5. Drive on_timer with known BPM, count event presence.
+
+#[test]
+fn vital_trend_rate_thresholds() {
+    use wifi_densepose_wasm_edge::vital_trend::VitalTrendAnalyzer;
+
+    // event ids: 101 brady-pnea, 102 tachy-pnea, 103 brady-cardia, 104 tachy-cardia, 105 apnea
+    fn drive_breathing(bpm: f32, n: u32) -> std::collections::HashSet<i32> {
+        let mut det = VitalTrendAnalyzer::new();
+        let mut seen = std::collections::HashSet::new();
+        for _ in 0..n {
+            for &(id, _) in det.on_timer(bpm, 72.0) {
+                seen.insert(id);
+            }
+        }
+        seen
+    }
+    fn drive_heart(bpm: f32, n: u32) -> std::collections::HashSet<i32> {
+        let mut det = VitalTrendAnalyzer::new();
+        let mut seen = std::collections::HashSet::new();
+        for _ in 0..n {
+            for &(id, _) in det.on_timer(16.0, bpm) {
+                seen.insert(id);
+            }
+        }
+        seen
+    }
+
+    // 6 calls > ALERT_DEBOUNCE(5) so a sustained abnormal value fires.
+    let mut c = Confusion::default();
+    // Bradypnea: <12 positive; normal 16 negative.
+    c.observe(drive_breathing(8.0, 6).contains(&101), true);
+    c.observe(drive_breathing(16.0, 6).contains(&101), false);
+    // Tachypnea: >25 positive; normal negative.
+    c.observe(drive_breathing(30.0, 6).contains(&102), true);
+    c.observe(drive_breathing(16.0, 6).contains(&102), false);
+    // Bradycardia: <50.
+    c.observe(drive_heart(40.0, 6).contains(&103), true);
+    c.observe(drive_heart(72.0, 6).contains(&103), false);
+    // Tachycardia: >120.
+    c.observe(drive_heart(140.0, 6).contains(&104), true);
+    c.observe(drive_heart(72.0, 6).contains(&104), false);
+    // Apnea: breathing < 1.0 for >= 20 calls.
+    c.observe(drive_breathing(0.0, 20).contains(&105), true);
+    c.observe(drive_breathing(0.0, 10).contains(&105), false); // only 10 calls -> below APNEA_SECONDS
+
+    c.report("vital_trend (brady/tachy-pnea/cardia, apnea)");
+    // All 5 thresholds + their negatives must classify correctly.
+    assert_eq!(c.accuracy(), 1.0, "vital_trend rate thresholds must be exact");
+}
+
+// ── 2. exo_time_crystal — period-doubling (sub-harmonic) detection ───────────
+// Detects a peak at lag L AND a peak at lag 2L in motion-energy autocorrelation.
+// PLANT positive: period-2 modulation (alternating amplitude on a base period)
+//   so autocorr has peaks at both L and 2L.
+// PLANT negative: a single clean period (peak at L only) or noise.
+
+fn run_time_crystal(motion: &[f32]) -> bool {
+    use wifi_densepose_wasm_edge::exo_time_crystal::TimeCrystalDetector;
+    let mut det = TimeCrystalDetector::new();
+    let mut detected = false;
+    for &m in motion {
+        for &(id, v) in det.process_frame(m) {
+            if id == 680 && v >= 2.0 {
+                detected = true; // CRYSTAL_DETECTED with multiplier 2
+            }
+        }
+    }
+    detected
+}
+
+#[test]
+fn exo_time_crystal_period_doubling() {
+    let n = 256usize;
+    // Positive: period-2 subharmonic. Base period P=16; alternate full periods
+    // are scaled differently so the waveform only repeats every 2P=32 (peak at
+    // lag 32) while still correlating at P=16. Plain sine (no abs, which would
+    // itself fold frequency and fake a sub-harmonic).
+    let base_p = 16.0f32;
+    let mut pos = Vec::with_capacity(n);
+    for t in 0..n {
+        let phase = (t as f32) * 2.0 * PI / base_p;
+        let sub = if ((t as f32 / base_p) as i32) % 2 == 0 { 1.0 } else { 0.45 };
+        pos.push(0.6 + 0.35 * phase.sin() * sub);
+    }
+    // HONEST LIMIT (measured below): a *pure* periodic signal already has
+    // autocorrelation peaks at L AND 2L (natural harmonics), so this detector
+    // cannot separate a true period-2 sub-harmonic from a plain periodic signal.
+    // The construct it CAN discriminate with known ground truth is
+    // "periodic-with-coordination vs aperiodic". We validate that.
+    //
+    // Negative 1: incrementing-seed pseudo-noise (no periodicity).
+    let mut noise = Vec::with_capacity(n);
+    let mut s: u32 = 12345;
+    for _ in 0..n {
+        s = s.wrapping_mul(1664525).wrapping_add(1013904223);
+        noise.push(0.3 + 0.4 * ((s >> 8) & 0xffff) as f32 / 65535.0);
+    }
+    // Negative 2: near-constant motion (no oscillation at all).
+    let flat: Vec<f32> = (0..n).map(|t| 0.5 + 1e-4 * (t as f32 * 0.01).sin()).collect();
+
+    let mut c = Confusion::default();
+    c.observe(run_time_crystal(&pos), true); // planted period-2 -> detect
+    c.observe(run_time_crystal(&noise), false); // pseudo-noise -> reject
+    c.observe(run_time_crystal(&flat), false); // flat -> reject
+    c.report("exo_time_crystal (periodic-coordination vs aperiodic)");
+    assert!(
+        run_time_crystal(&pos),
+        "must detect planted period-2 coordinated motion"
+    );
+    assert!(
+        !run_time_crystal(&noise),
+        "must NOT fire on pseudo-noise"
+    );
+    assert!(!run_time_crystal(&flat), "must NOT fire on flat motion");
+}
+
+// ── 3. exo_ghost_hunter — hidden breathing (autocorr at breathing-range lag) ─
+// When presence==0, aggregate phase is autocorrelated at lags 5..=15; a peak
+// there above HIDDEN_PRESENCE_THRESHOLD(0.3) emits HIDDEN_PRESENCE(652).
+// PLANT positive: phase sinusoid at a lag in [5,15] across an empty room.
+// PLANT negative: flat phase (no periodic breathing signature).
+
+fn run_ghost_hidden_breathing(period: f32, amp: f32, frames: usize) -> f32 {
+    use wifi_densepose_wasm_edge::exo_ghost_hunter::GhostHunterDetector;
+    let mut det = GhostHunterDetector::new();
+    let n_sc = 32usize;
+    let mut max_hidden = 0.0f32;
+    for t in 0..frames {
+        let breath = if period > 0.0 {
+            amp * (t as f32 * 2.0 * PI / period).sin()
+        } else {
+            0.0
+        };
+        let mut phases = [0.0f32; 32];
+        let mut amps = [0.0f32; 32];
+        let mut vars = [0.0f32; 32];
+        for i in 0..n_sc {
+            // breathing modulates phase uniformly (chest motion -> common phase shift)
+            phases[i] = 0.1 * (i as f32 * 0.2).sin() + breath;
+            amps[i] = 1.0;
+            vars[i] = 0.01;
+        }
+        // presence = 0 (empty room) is required for the hidden-breathing path.
+        for &(id, v) in det.process_frame(&phases, &amps, &vars, 0, 0.0) {
+            if id == 652 {
+                if v > max_hidden {
+                    max_hidden = v;
+                }
+            }
+        }
+    }
+    max_hidden
+}
+
+#[test]
+fn exo_ghost_hunter_hidden_breathing() {
+    // Period 8 frames is within the breathing lag window [5,15].
+    let pos = run_ghost_hidden_breathing(8.0, 0.5, 200);
+    // Flat phase (no breathing) -> no hidden-presence event.
+    let neg = run_ghost_hidden_breathing(0.0, 0.0, 200);
+
+    let mut c = Confusion::default();
+    c.observe(pos > 0.0, true);
+    c.observe(neg > 0.0, false);
+    c.report("exo_ghost_hunter (hidden breathing, lag 8)");
+    println!(
+        "  detail: planted-breathing hidden-presence score={:.3}, flat-phase score={:.3}",
+        pos, neg
+    );
+    assert!(
+        pos > 0.3,
+        "planted breathing must score above HIDDEN_PRESENCE_THRESHOLD (0.3); got {}",
+        pos
+    );
+    assert!(
+        neg <= 0.0,
+        "flat phase must not emit hidden presence; got {}",
+        neg
+    );
+}
+
+// ── 4. occupancy — calibration + variance-driven zone occupancy ──────────────
+// BASELINE_FRAMES=200 of low-variance amplitudes establish baseline; then
+// high amplitude-variance per zone (score > ZONE_THRESHOLD=0.02) flips a zone
+// to occupied (EVENT_ZONE_OCCUPIED=300).
+
+#[test]
+fn occupancy_variance_detection() {
+    use wifi_densepose_wasm_edge::occupancy::OccupancyDetector;
+
+    fn run(occupied_signal: bool) -> bool {
+        let mut det = OccupancyDetector::new();
+        let n_sc = 32usize;
+        let mut phases = [0.0f32; 32];
+        // Calibration: 220 frames of near-flat amplitudes (low variance).
+        for t in 0..220 {
+            let mut amps = [1.0f32; 32];
+            for i in 0..n_sc {
+                amps[i] = 1.0 + 1e-3 * ((t + i) as f32 * 0.7).sin();
+                phases[i] = 0.01 * (i as f32).sin();
+            }
+            det.process_frame(&phases, &amps);
+        }
+        // Test phase: 60 frames. If occupied, inject strong per-zone amplitude
+        // variance; else keep flat.
+        let mut fired = false;
+        for t in 0..60 {
+            let mut amps = [1.0f32; 32];
+            for i in 0..n_sc {
+                amps[i] = if occupied_signal {
+                    // strong structured variance within each zone
+                    1.0 + 2.0 * (((i % 4) as f32) - 1.5) + 0.5 * (t as f32 * 0.3 + i as f32).sin()
+                } else {
+                    1.0 + 1e-3 * ((t + i) as f32 * 0.7).sin()
+                };
+            }
+            for &(id, _) in det.process_frame(&phases, &amps) {
+                if id == 300 {
+                    fired = true;
+                }
+            }
+        }
+        fired
+    }
+
+    let mut c = Confusion::default();
+    c.observe(run(true), true);
+    c.observe(run(false), false);
+    c.report("occupancy (zone variance vs flat baseline)");
+    assert!(run(true), "high zone variance after calibration must occupy a zone");
+    assert!(!run(false), "flat amplitude must stay unoccupied");
+}
+
+// ── 5. intrusion — calibrate, arm, then disturbance>=0.8 alerts ──────────────
+// disturbance = 0.6*frac(|Δphase|>1.5) + 0.4*frac(|Δamp|>3σ). Calibrate 200
+// quiet frames, monitor 100 quiet frames -> Armed, then 3 frames of large
+// phase+amp disturbance -> EVENT_INTRUSION_ALERT(200).
+
+#[test]
+fn intrusion_disturbance_alert() {
+    use wifi_densepose_wasm_edge::intrusion::IntrusionDetector;
+
+    fn run(intrude: bool) -> bool {
+        let mut det = IntrusionDetector::new();
+        let n_sc = 32usize;
+        // Calibration (200) + monitoring quiet (120) -> Armed. Quiet = constant.
+        for _ in 0..330 {
+            let phases = [0.5f32; 32];
+            let amps = [1.0f32; 32];
+            det.process_frame(&phases, &amps);
+        }
+        let mut alerted = false;
+        // 10 test frames.
+        for t in 0..10 {
+            let mut phases = [0.5f32; 32];
+            let mut amps = [1.0f32; 32];
+            if intrude {
+                for i in 0..n_sc {
+                    // alternate phase by 3.0 (>1.5) and amplitude far from baseline 1.0.
+                    phases[i] = if t % 2 == 0 { 0.5 } else { 4.0 };
+                    amps[i] = 1.0 + 8.0; // huge deviation vs ~0 baseline variance
+                }
+            }
+            for &(id, _) in det.process_frame(&phases, &amps) {
+                if id == 200 {
+                    alerted = true;
+                }
+            }
+        }
+        alerted
+    }
+
+    let mut c = Confusion::default();
+    c.observe(run(true), true);
+    c.observe(run(false), false);
+    c.report("intrusion (armed -> disturbance alert vs quiet)");
+    assert!(run(true), "large phase+amplitude disturbance must alert when armed");
+    assert!(!run(false), "quiet environment must not alert");
+}
+
+// ── 6. sig_sparse_recovery — ISTA recovery of planted null subcarriers ───────
+// Initialize correlation on clean frames, then null >10% of subcarriers and
+// MEASURE how well ISTA recovers them (rate-error style: recovery residual).
+
+#[test]
+fn sig_sparse_recovery_recovers_nulls() {
+    use wifi_densepose_wasm_edge::sig_sparse_recovery::SparseRecovery;
+
+    let mut det = SparseRecovery::new();
+    let n_sc = 32usize;
+    // Underlying smooth signal (neighbor-correlated) the model can learn.
+    let truth: Vec<f32> = (0..n_sc).map(|i| 1.0 + 0.5 * (i as f32 * 0.4).sin()).collect();
+
+    // Warm up correlation model with 30 clean frames.
+    for _ in 0..30 {
+        let mut amps: Vec<f32> = truth.clone();
+        det.process_frame(&mut amps);
+    }
+
+    // Null subcarriers 5..13 (8/32 = 25% > MIN_DROPOUT_RATE 0.10).
+    let mut amps: Vec<f32> = truth.clone();
+    let nulled: Vec<usize> = (5..13).collect();
+    for &i in &nulled {
+        amps[i] = 0.0;
+    }
+    // Baseline error if the nulls were left at 0.0 (unrecovered).
+    let mut sse0 = 0.0f32;
+    for &i in &nulled {
+        sse0 += truth[i] * truth[i];
+    }
+    let baseline_rmse = (sse0 / nulled.len() as f32).sqrt();
+
+    let mut recovery_seen = false;
+    for &(id, _) in det.process_frame(&mut amps) {
+        if id == 715 {
+            recovery_seen = true; // RECOVERY_COMPLETE
+        }
+    }
+    // Measure recovery error on the nulled positions (now written back in-place).
+    let mut sse = 0.0f32;
+    for &i in &nulled {
+        let d = amps[i] - truth[i];
+        sse += d * d;
+    }
+    let rmse = (sse / nulled.len() as f32).sqrt();
+    println!(
+        "MEASURED-on-synthetic | {:<34} | dropout-detect+recovery-trigger=PASS | recovered RMSE={:.4} vs unrecovered-null RMSE={:.4} ({:+.1}%) over {} nulled subcarriers",
+        "sig_sparse_recovery (ISTA)",
+        rmse,
+        baseline_rmse,
+        100.0 * (1.0 - rmse / baseline_rmse),
+        nulled.len()
+    );
+    // CONSTRUCTIBLE + MEASURED: the dropout detection and recovery-trigger
+    // pipeline fires correctly on >10% planted nulls. This is the validatable
+    // claim and we assert it.
+    assert!(recovery_seen, "dropout > 10% must trigger ISTA recovery (RECOVERY_COMPLETE)");
+    // HONEST MEASURED RESULT (reported, NOT asserted as a win): on this
+    // neighbor-correlated synthetic signal the tridiagonal-model ISTA recovery
+    // does NOT beat leaving the nulls at zero (RMSE ~1.00 vs ~0.98). The skill's
+    // *recovery accuracy* is therefore NOT validated as effective on synthetic
+    // data — only its dropout-detection/trigger path is. Reported in RESULTS.md.
+    assert!(
+        rmse.is_finite() && rmse < 5.0,
+        "recovered values must be finite and bounded; got {}",
+        rmse
+    );
+}
+
+// ── 7. exo_rain_detect — broadband variance onset (empty room) ───────────────
+// presence=0, MIN_EMPTY_FRAMES=40 baseline, then >=6/8 groups with variance
+// ratio > 2.5 for ONSET_FRAMES=10 -> EVENT_RAIN_ONSET(660).
+
+#[test]
+fn exo_rain_detect_broadband_onset() {
+    use wifi_densepose_wasm_edge::exo_rain_detect::RainDetector;
+
+    fn run(rain: bool) -> bool {
+        let mut det = RainDetector::new();
+        let n_sc = 32usize;
+        let phases = [0.1f32; 32];
+        let amps = [1.0f32; 32];
+        // 60 empty baseline frames with low variance.
+        for _ in 0..60 {
+            let vars = [0.001f32; 32];
+            det.process_frame(&phases, &vars, &amps, 0);
+        }
+        let mut onset = false;
+        // 40 frames: broadband-high variance if rain, else stay low.
+        for _ in 0..40 {
+            let vars = if rain { [0.5f32; 32] } else { [0.001f32; 32] };
+            for &(id, _) in det.process_frame(&phases, &vars, &amps, 0) {
+                if id == 660 {
+                    onset = true;
+                }
+            }
+        }
+        let _ = n_sc;
+        onset
+    }
+
+    let mut c = Confusion::default();
+    c.observe(run(true), true);
+    c.observe(run(false), false);
+    c.report("exo_rain_detect (broadband variance onset)");
+    assert!(run(true), "broadband variance elevation must trigger rain onset");
+    assert!(!run(false), "stable low variance must not trigger rain");
+}
+
+// ── 8. sig_flash_attention — peak-attention subcarrier localization ──────────
+// Q=mean(phase) per group, K=mean(prev_phase), score=Q*K/sqrt(8), softmax peak.
+// Plant a sustained large phase in a KNOWN group -> assert that group becomes
+// the reported attention peak (EVENT_ATTENTION_PEAK_SC=700).
+
+#[test]
+fn sig_flash_attention_peak_localization() {
+    use wifi_densepose_wasm_edge::sig_flash_attention::FlashAttention;
+
+    fn peak_for_group(target_group: usize) -> i32 {
+        let mut det = FlashAttention::new();
+        let n_sc = 32usize;
+        let subs_per = n_sc / 8;
+        let mut last_peak = -1;
+        // Sustain the spike so both Q (this frame) and K (prev frame) are large
+        // in the target group -> highest score there.
+        for _ in 0..20 {
+            let mut phases = [0.05f32; 32];
+            let mut amps = [1.0f32; 32];
+            for i in (target_group * subs_per)..((target_group + 1) * subs_per) {
+                phases[i] = 3.0;
+                amps[i] = 3.0;
+            }
+            for &(id, v) in det.process_frame(&phases, &amps) {
+                if id == 700 {
+                    last_peak = v as i32;
+                }
+            }
+        }
+        last_peak
+    }
+
+    let mut correct = 0u32;
+    let total = 8u32;
+    for g in 0..8usize {
+        let got = peak_for_group(g);
+        if got == g as i32 {
+            correct += 1;
+        }
+        println!("  flash_attention: planted group {} -> reported peak {}", g, got);
+    }
+    let acc = correct as f32 / total as f32;
+    println!(
+        "MEASURED-on-synthetic | {:<34} | peak-localization accuracy = {}/{} = {:.3}",
+        "sig_flash_attention", correct, total, acc
+    );
+    assert!(acc >= 0.75, "must localize the planted attention group in >=75% of cases; got {}", acc);
+}
+
+// ── 9. spt_spiking_tracker — phase-delta zone localization ───────────────────
+// LIF neurons fire on |phase - prev_phase|; zone with most spikes is tracked
+// (EVENT_TRACK_UPDATE=770 carries zone id). Plant motion in a KNOWN zone.
+
+#[test]
+fn spt_spiking_tracker_zone_localization() {
+    use wifi_densepose_wasm_edge::spt_spiking_tracker::SpikingTracker;
+
+    fn track_zone(target_zone: usize) -> i32 {
+        let mut det = SpikingTracker::new();
+        let n_sc = 32usize;
+        let per = n_sc / 4; // 4 zones of 8 subcarriers
+        let mut prev = [0.0f32; 32];
+        let mut last_zone = -1;
+        // SPARSE plant: each zone's output neuron sums home-weight 1.0 + cross
+        // 0.25. Firing all 8 inputs (8*0.25=2.0) overdrives EVERY zone, so the
+        // tracker collapses to zone 0. Firing only 2 inputs in the target zone
+        // gives potential 2.0 at home (fires) but 0.5 cross (silent) -> only the
+        // target zone fires. This is the genuinely-constructible localization.
+        let base = target_zone * per;
+        for t in 0..60 {
+            let mut phases = [0.0f32; 32];
+            // 2 subcarriers in the target zone get a large alternating delta.
+            for k in 0..2 {
+                phases[base + k] = if t % 2 == 0 { 0.0 } else { 3.0 };
+            }
+            for &(id, v) in det.process_frame(&phases, &prev) {
+                if id == 770 {
+                    last_zone = v as i32;
+                }
+            }
+            prev.copy_from_slice(&phases);
+        }
+        last_zone
+    }
+
+    let mut correct = 0u32;
+    for z in 0..4usize {
+        let got = track_zone(z);
+        if got == z as i32 {
+            correct += 1;
+        }
+        println!("  spiking_tracker: planted zone {} -> tracked zone {}", z, got);
+    }
+    let acc = correct as f32 / 4.0;
+    println!(
+        "MEASURED-on-synthetic | {:<34} | zone-localization accuracy = {}/4 = {:.3}",
+        "spt_spiking_tracker", correct, acc
+    );
+    assert!(acc >= 0.75, "must track the planted motion zone in >=75% of cases; got {}", acc);
+}
+
+// ── 10. sig_optimal_transport — distribution-shift detection ─────────────────
+// Sliced Wasserstein over amplitudes; sustained shift > WASS_SHIFT(0.25) for
+// SHIFT_DEB(3) -> EVENT_DISTRIBUTION_SHIFT(726). Plant a large vs no shift.
+
+#[test]
+fn sig_optimal_transport_distribution_shift() {
+    use wifi_densepose_wasm_edge::sig_optimal_transport::OptimalTransportDetector;
+
+    fn run(shift: bool) -> bool {
+        let mut det = OptimalTransportDetector::new();
+        let n_sc = 32usize;
+        // Establish a reference distribution.
+        let base: Vec<f32> = (0..n_sc).map(|i| i as f32 * 0.1).collect();
+        for _ in 0..10 {
+            let mut a = base.clone();
+            det.process_frame(&mut a);
+        }
+        let mut shifted = false;
+        // The detector compares each frame to the PREVIOUS frame (prev_amps is
+        // updated every frame), so a one-time jump decays. To exceed WASS_SHIFT
+        // (0.25) for SHIFT_DEB(3) consecutive frames we need a sustained large
+        // frame-to-frame change: alternate between two very different
+        // distributions each frame.
+        for t in 0..15 {
+            let mut a: Vec<f32> = if shift {
+                if t % 2 == 0 {
+                    base.clone()
+                } else {
+                    base.iter().map(|x| 10.0 - x).collect() // reversed + offset
+                }
+            } else {
+                base.clone()
+            };
+            for &(id, _) in det.process_frame(&mut a) {
+                if id == 726 {
+                    shifted = true;
+                }
+            }
+        }
+        shifted
+    }
+
+    let mut c = Confusion::default();
+    c.observe(run(true), true);
+    c.observe(run(false), false);
+    c.report("sig_optimal_transport (distribution shift)");
+    assert!(run(true), "large amplitude-distribution shift must be detected");
+    assert!(!run(false), "stationary distribution must not flag a shift");
+}
+
+// ── 11. lrn_dtw_gesture_learn — enroll a template, replay match vs reject ────
+// STILLNESS_FRAMES=60 stillness, then 3 rehearsals of the same gesture
+// (motion->stillness) -> EVENT_GESTURE_LEARNED(730). Replaying the learned
+// gesture later (in Idle) -> EVENT_GESTURE_MATCHED(731); replaying a different
+// gesture -> no match.
+
+#[test]
+fn lrn_dtw_gesture_learn_enroll_and_match() {
+    use wifi_densepose_wasm_edge::lrn_dtw_gesture_learn::GestureLearner;
+
+    // A gesture is a phase trajectory across frames; motion_energy gates the
+    // enroll state machine (still < 0.05, moving >= 0.05).
+    fn gesture_frame(kind: u8, step: usize) -> ([f32; 32], f32) {
+        let mut phases = [0.0f32; 32];
+        let s = step as f32;
+        for i in 0..32 {
+            phases[i] = match kind {
+                // distinct trajectories
+                0 => (s * 0.4 + i as f32 * 0.1).sin(),
+                _ => (s * 0.9 + i as f32 * 0.05).cos() * 1.5,
+            };
+        }
+        (phases, 0.5) // moving
+    }
+
+    let mut det = GestureLearner::new();
+    let still = ([0.0f32; 32], 0.0f32);
+
+    // helper to feed N still frames
+    let feed_still = |det: &mut GestureLearner, n: usize| {
+        for _ in 0..n {
+            det.process_frame(&still.0, still.1);
+        }
+    };
+    let feed_gesture = |det: &mut GestureLearner, kind: u8, len: usize| -> bool {
+        let mut learned = false;
+        for s in 0..len {
+            let (ph, me) = gesture_frame(kind, s);
+            for &(id, _) in det.process_frame(&ph, me) {
+                if id == 730 {
+                    learned = true;
+                }
+            }
+        }
+        learned
+    };
+
+    // Enroll gesture kind 0: stillness, then 3 identical rehearsals (each
+    // motion burst followed by stillness).
+    feed_still(&mut det, 70);
+    let mut any_learned = false;
+    for _ in 0..3 {
+        any_learned |= feed_gesture(&mut det, 0, 30);
+        feed_still(&mut det, 70);
+    }
+
+    // Replay the SAME gesture during Idle -> expect a match (731).
+    let mut matched_same = false;
+    for s in 0..30 {
+        let (ph, me) = gesture_frame(0, s);
+        for &(id, _) in det.process_frame(&ph, me) {
+            if id == 731 {
+                matched_same = true;
+            }
+        }
+    }
+    feed_still(&mut det, 70);
+    // Replay a DIFFERENT gesture -> ideally no match (731) to the learned one.
+    let mut matched_diff = false;
+    for s in 0..30 {
+        let (ph, me) = gesture_frame(1, s);
+        for &(id, _) in det.process_frame(&ph, me) {
+            if id == 731 {
+                matched_diff = true;
+            }
+        }
+    }
+
+    let tmpl_count = det.template_count();
+    println!(
+        "MEASURED-on-synthetic | {:<34} | learned_event={} templates={} match_same={} match_different={}",
+        "lrn_dtw_gesture_learn", any_learned, tmpl_count, matched_same, matched_diff
+    );
+    // The enroll path must complete (a template is learned from 3 identical
+    // rehearsals). Whether the precise replay matches is the DTW behavior we
+    // measure and report; we assert the deterministic enrollment.
+    assert!(
+        any_learned || tmpl_count > 0,
+        "3 identical rehearsals after stillness must enroll a template"
+    );
+}
+
+// ── 12. sig_mincut_person_match — stable id assignment for distinct signatures ─
+// Per-person feature = top-FEAT_DIM variances in that person's spatial region.
+// Two persons with DISTINCT, stable variance signatures should get stable ids
+// (EVENT_PERSON_ID_ASSIGNED=720) with zero swaps across frames.
+
+#[test]
+fn sig_mincut_person_stable_ids() {
+    use wifi_densepose_wasm_edge::sig_mincut_person_match::PersonMatcher;
+
+    let mut det = PersonMatcher::new();
+    let n_sc = 32usize;
+    let amplitudes = [1.0f32; 32];
+    let mut swaps = 0u32;
+    let mut assigned = false;
+
+    // 40 frames, 2 persons: person 0 region (0..16) high-variance signature,
+    // person 1 region (16..32) low-variance signature, both stable.
+    for _ in 0..40 {
+        let mut variances = [0.0f32; 32];
+        for i in 0..n_sc {
+            variances[i] = if i < 16 {
+                2.0 + 0.05 * (i as f32).sin()
+            } else {
+                0.2 + 0.01 * (i as f32).cos()
+            };
+        }
+        for &(id, _) in det.process_frame(&amplitudes, &variances, 2) {
+            if id == 720 {
+                assigned = true;
+            }
+            if id == 721 {
+                swaps += 1;
+            }
+        }
+    }
+    println!(
+        "MEASURED-on-synthetic | {:<34} | assigned={} id_swaps_over_40_frames={}",
+        "sig_mincut_person_match", assigned, swaps
+    );
+    assert!(assigned, "distinct stable signatures must assign person ids");
+    assert!(swaps == 0, "stable distinct signatures must not swap ids; got {} swaps", swaps);
+}
Author	SHA1	Message	Date
rUv	74ecce3218	Merge pull request #1048 from ruvnet/fix/issues-1031-894-fusion-guard-model-load fix: multistatic fusion guard for real TDM (#1031) + load published HF model via auto-detect/convert (#894)	2026-06-13 12:23:06 -04:00
ruv	fd1430e46f	test(engine): update contradiction_demotes_privacy for #1031 guard thresholds The streaming-engine privacy-demotion test fed a 2 ms timestamp spread, which demoted under the old 1 ms soft guard. #1031 raised the default soft guard to 20 ms (to accommodate the real TDM slot offset), so 2 ms now fuses cleanly with no demotion. Bump the test spread to 25 ms (above the 20 ms soft guard, within the 60 ms hard guard) so it still proves the ADR-137 -> ADR-141 demotion wiring. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-13 12:14:11 -04:00
ruv	107232c0be	fix(sensing-server): load published HuggingFace model via RVF auto-detect+convert (#894 ) ProgressiveLoader rejected the published ruvnet/wifi-densepose-pretrained model with the opaque "invalid magic at offset 0: expected 0x52564653 (RVFS), got 0x77455735", then silently fell back to signal heuristics (the "10 persons for 1" garbage reporters saw). The HF repo ships model.safetensors, model-q{2,4,8}.bin (magic 0x77455735 = "5WEw"), and model.rvf.jsonl -- none carry the binary-RVF magic the loader wants. - New model_format module: auto-detects RVFS / safetensors / HF-quant-bin / JSONL by magic+name; returns a typed actionable ModelLoadError (lists accepted formats + the one-command convert path, never the opaque magic); converts safetensors / model.rvf.jsonl -> RVF in-memory so the published full-precision model loads via --model. - load_or_convert_model: native RVF first, else auto-detect+convert+load, else typed error. The silent heuristics fallback is now a loud, actionable message. - --convert-model <in> --convert-out <out> CLI subcommand: one-command offline conversion, verifies the output loads before writing. - #1031 env seam: WDP_TDM_SLOTS + WDP_TDM_SLOT_US derive the multistatic guard from a deployment TDM schedule (default 60 ms / 20 ms otherwise). Honest scope: the converter wires the format/load path (safetensors F32 tensors -> RVF weight segment, manifest written, Layer A/B/C succeed, weights round-trip). It does NOT claim end-to-end pose accuracy -- the HF pose-decoder architecture differs from this crate inference head (data-gated in #894). Quantized .bin blobs are rejected with a typed error pointing at safetensors. Tests (fail on the old opaque-magic path): - model_format::safetensors_converts_and_loads - model_format::hf_quant_classifies_to_actionable_error - model_format::{jsonl_converts_and_loads, convert_to_rvf_dispatches_and_rejects_quant, ...} Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-13 12:05:05 -04:00
ruv	287885776b	fix(signal): multistatic fusion guard too tight for real TDM hardware (#1031 ) MultistaticConfig::default().guard_interval_us was 5_000 us (5 ms) with a comment claiming "well within the 50 ms TDMA cycle". That is wrong: on an N-slot TDM schedule node k transmits in slot k, so two nodes are separated by the slot offset, not clock jitter. A real 2-node mesh (slots 0/1) measured an 18,194 us spread, so every real frame set exceeded the 5 ms guard and fuse() silently fell back to per-node sum/dedup -- multistatic fusion never ran on hardware. - Raise default hard guard to 60 ms (full 50 ms TDMA cycle + 20% jitter headroom, derived from the slot model and documented in the field doc). - Raise soft guard to 20 ms (just above the observed 18.2 ms 2-slot spread). - Add MultistaticConfig::for_tdm_schedule(total_slots, slot_duration_us). - Keep the honest per-node fallback for genuinely-mismatched frames. Tests (fail on the old 5 ms default): - fuse_real_tdm_spread_18194us_fuses_with_default_guard - configurable_guard_rejects_too_large_spread - for_tdm_schedule_invariants Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-13 12:04:47 -04:00
rUv	29e937ef52	Merge pull request #1044 from ruvnet/feat/edge-skills-synthetic-validation feat(wasm-edge): unified EdgePipeline (all ~64 skills) + honest synthetic validation harness	2026-06-13 00:46:29 -04:00
ruv	41665d3de9	test(wasm-edge): synthetic-ground-truth validation harness for edge skills (ADR-160) Plant signals with known answers, run the real detector, MEASURE detection accuracy / precision / recall / rate-error — synthetic-ground-truth ONLY, not field accuracy. MEASURED-on-synthetic (12 tests, all green): - vital_trend, exo_ghost_hunter(hidden breathing), occupancy, intrusion, exo_rain_detect, sig_optimal_transport: acc 1.000 - exo_time_crystal: 1.000 on periodic-vs-aperiodic (its sub-harmonic-vs-clean- period claim is NOT separable by autocorrelation — recorded honestly) - sig_flash_attention: 8/8 peak localization; spt_spiking_tracker: 4/4 zone localization (sparse plant); sig_mincut_person_match: 0 id-swaps/40 frames - lrn_dtw_gesture_learn: enrollment validated (replay-match reported, not asserted) - sig_sparse_recovery: trigger validated; recovery accuracy reported NEGATIVE (-2.2% vs unrecovered baseline) — only its detect/trigger path is validated DATA-GATED (listed, NOT faked): med_seizure/apnea/cardiac/respiratory/gait, sec_weapon_detect, exo_emotion/happiness/dream_stage/gesture_language — each needs real labelled clinical/affect/ASL/metal-object data; no number claimed. benchmarks/edge-skills/RESULTS.md documents every result + reproduce command and the explicit honesty boundary. ADR-160 deferred 'per-skill accuracy validation' item updated to PARTIALLY MEASURED-on-synthetic + DATA-GATED. Suite: 631 passed default / 669 medical, 0 failed. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-13 00:33:51 -04:00
ruv	c6eacb7ff8	feat(wasm-edge): unified EdgePipeline wiring all ~64 edge skills (ADR-160) Register every runtime skill module behind one uniform EdgeSkill trait and run them all per CSI frame, aggregating (skill, event_id, value) triples. - src/pipeline_all.rs: CsiFrameView (borrowed per-frame inputs), EdgeSkill trait, EdgePipeline (Box<dyn> dispatch over all skills), SkillEvent/SkillInfo introspection. Host-only (std); the wasm no_std build keeps the flagship lib.rs pipeline. - src/skill_registry.rs: per-skill adapters (fwd_skill! direct-forward + synth_skill! for non-tuple returns). No skill DSP changed — only call wiring. gesture/coherence/adversarial synthesize one event; sig_sparse_recovery gets an owned mutable amplitude scratch; timer skills driven once per frame. - med_* tier registered only under --features medical-experimental (preserves the ADR-160 safety gate). Default tier = 59 skills; +medical = 64. - tests/pipeline_all.rs: 4 tests — all skills run without panic over 300 deterministic synthetic frames, every emitted id is declared by its skill, introspection well-formed, default tier excludes medical (59) / medical adds 5 (64). - examples/run_all_skills.rs: runnable demo printing per-skill event totals. Full suite: 619 passed default (615 M6 baseline + 4 new), 0 failed. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-13 00:20:29 -04:00
rUv	153bc0595b	Merge pull request #1043 from ruvnet/docs/adr-gap-remediation-1 docs(adr): Gap Register remediation — write phantom ADR-132/165, fix ADR-134 collision, correct statuses	2026-06-12 23:11:10 -04:00
ruv	8fd4ee917d	docs(adr): mark ADR-164 Gap Register items resolved (G3, G5) + correct G2 Records the remediation done in this branch: - G3 (homecore-recorder/migrate phantom ADRs) → RESOLVED: ADR-132 + ADR-165 written. - G5 (10 streaming-engine Proposed-while-built) → RESOLVED: 136-145 flipped to "Accepted — partial", with the honest caveat that the notes describe building blocks built+tested, not live-path integration. - G2 (missing Status headers) → corrected: ADR-134-CIR was mislabeled as missing (it has a Status row); the 2 genuine misses (147-benchmark-proof, 052-ddd) are both inside owner-gated duplicate-number collisions, so left untouched. Early ADRs using "\| Status \|" vs "\| Status \|" are different-format-but-present. Net: 0 status headers added. - Updated Coverage-Gaps bullets for recorder/migrate. Renumbering/dedup of the 6 collisions left owner-gated, as instructed. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-12 23:01:10 -04:00
ruv	5c5112db0e	docs(adr): correct streaming-engine statuses 136-145 Proposed→Accepted — ADR-164 G5 All 10 streaming-engine ADRs (136-145) carried Status: Proposed while each has a concrete commit-pinned "Built -- tested building block" Implementation-Status note (136: 11f89727f; 137: 4fa3847ac; 138: fc7674bde; 139: 521a012d8; 140: 169a355bd; 141: 7d88eb84c; 142: 1f8e180d6; 143: 2d4f3dea5; 144: b10bc2e9a; 145: `0f336b7d3`), each with a test count. Flipped each to "Accepted — partial (built + tested building block; integration glue pending — see Implementation Status, commit <hash>)". Honest "partial", not full Accepted: the notes themselves state the blocks are tested+compiling but "mostly not yet on the live 20 Hz path". 143 (v2 dataset-gated) and 144 (no UWB radio in fleet) carry their specific residual gates inline. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-12 23:00:54 -04:00
ruv	e3696da8d8	docs(adr): write ADR-165 (HOMECORE-MIGRATE), repoint migrate 134→165 — ADR-164 G3 homecore-migrate cited "ADR-134 (HOMECORE-MIGRATE)", but on-disk ADR-134 is "First-Class CIR Support" — a different decision. The migrate crate was governed by a phantom identity (ADR-164 Gap G3). - New ADR-165-homecore-migrate-from-home-assistant.md (next free number), reverse-documented from the shipped P1 scaffold: HA .storage reader, versioned format gate (unknown minor_version = hard error), per-artifact parsers, inspect CLI, structured errors. Status: Accepted — P1 scaffold (full conversion P2). Trust-boundary rationale for the untrusted .storage import is the centerpiece. - Repointed every ADR-134 governing reference in v2/crates/homecore-migrate/ (Cargo.toml, README.md, src/lib.rs, src/config_entries.rs, src/storage_format/mod.rs) → ADR-165. Left the ADR-132 (recorder-feature) refs intact. Explanatory renumber notes retained. - On-disk ADR-134 (CIR) untouched. ADR-126 series-map registry row owner-gated. Docs/comments only — cargo build -p homecore-migrate --no-default-features still compiles. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-12 23:00:33 -04:00
ruv	9457d441b2	docs(adr): write missing ADR-132 (HOMECORE-RECORDER) — resolves ADR-164 G3 homecore-recorder cites "ADR-132" in Cargo.toml/README/lib.rs/schema.rs/ semantic.rs, but no ADR-132 file existed — the durable-state backbone was ungoverned (ADR-164 Gap G3 / Coverage-Gaps Lens A). Reverse-documented from the shipped, tested crate (not invented): SQLite HA-compatible recorder schema v48 (P1, 14 tests), ruvector HNSW semantic index (P2, feature-gated, 20 tests), hash-embedding honesty note, P3 real embeddings planned. Status: Accepted (shipped). Filename matches the link the crate README already pointed at. Documented retroactively; honest about hash-embedding limits and unbenchmarked latency targets. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-12 23:00:15 -04:00
rUv	626b4b2e97	Merge pull request #1042 from ruvnet/docs/adr-164-gap-analysis docs(adr): ADR-164 — ADR corpus gap analysis & remediation backlog (162 ADRs)	2026-06-12 22:47:21 -04:00
ruv	260fceefe9	docs(adr): ADR-164 corpus gap analysis + research notes (162 ADRs) Parallel gap analysis of all 162 ADRs (14-agent workflow): status distribution, prioritized Gap Register, supersession integrity, contradictions/retractions (anti-slop centerpiece), coverage gaps, and the honestly-gated backlog. Key findings: 6 duplicate ADR numbers + 3 missing Status headers (breaks the index); shipped crates citing phantom governing ADRs (homecore-recorder->ADR-132 nonexistent, homecore-migrate->ADR-134 mis-identified); streaming-engine ADRs 136-145 marked Proposed but actually Built; open ADR-080 sensing-server security findings never closed; ~64 proposed-only ADRs; pre-ADR-155 accuracy claims are CLAIMED not MEASURED. Detail in docs/adr/gap-analysis/{census,lens-findings}.md. Co-Authored-By: claude-flow <ruv@ruv.net>	2026-06-12 22:40:32 -04:00