Merge pull request #1044 from ruvnet/feat/edge-skills-synthetic-validation

feat(wasm-edge): unified EdgePipeline (all ~64 skills) + honest synthetic validation harness
test(wasm-edge): synthetic-ground-truth validation harness for edge skills (ADR-160)
2026-06-13 10:53:20 +00:00 · 2026-06-13 00:46:29 -04:00 · 2026-06-13 00:33:51 -04:00 · 2026-06-13 00:20:29 -04:00 · 2026-06-12 23:11:10 -04:00 · 2026-06-12 23:01:10 -04:00
26 changed files with 2382 additions and 29 deletions
@@ -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`
@@ -51,10 +51,10 @@ Severity: CRITICAL (corpus integrity / tooling-breaking / life-safety / security
 | 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) | CRITICAL | 147-benchmark-proof, 052-ddd-appendix, 134-CIR | add canonical `## Status`; relocate 147-proof to `benchmarks/`; label 052-ddd as appendix |
-| G3 | Shipped crates cite a non-existent or wrong-identity governing ADR | CRITICAL | homecore-recorder→"ADR-132" (no file); homecore-migrate→"ADR-134" (file is CIR) | write-missing-ADR (HOMECORE-RECORDER, HOMECORE-MIGRATE) |
+| 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 | HIGH | 136–145 | mark-stale → "Accepted — partial (integration glue pending)" (one batch) |
+| 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" |
@@ -91,8 +91,8 @@ The four CRITICAL items are the corpus's load-bearing AI-slop admissions — eac

 ## 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.
- **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).
+- ~~**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.
@@ -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/).
@@ -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).
@@ -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	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