mirror of
https://github.com/ruvnet/RuView
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Claude
9109269329
ADR-263 (@ruvnet/ruview 0.2.0), O1-O9: - claim-check fails closed on empty input (CLI exit 2, empty_text tool error) - MCP stdio server dispatches tools/call asynchronously (promise-based spawn); ping answers while a 3s fake verify runs — pinned by new e2e test - optionalDependencies dropped: cold npx installs exactly 1 package (MEASURED: was 4 pkgs/620kB/71 files via npm i in a clean prefix) - bounded rolling output tails replace spawnSync 1MiB maxBuffer - node_monitor port passed via sys.argv, never spliced into python -c source - serverInfo.version read from package.json; resources/prompts stubs - skills single-sourced: prepack sync script generates .claude/skills/ copies - which() = memoized dep-free PATH scan - tools underscore-canonical (ruview_claim_check, ...) + dotted aliases - guardrail precision: word-boundary map/f1/auc/iou, code-span + F1/O2 label scrubbing, quantitative-claims-only; packaging reproducer hints - 30/30 tests (was 17), incl. concurrency e2e + fail-open regression pins ADR-264 (@ruvnet/rvagent 0.2.0), O1-O9: - exports fixed: types-first, phantom dist/index.cjs require target removed - tarball map-free: 127,704B unpacked / 46 files / 0 maps (MEASURED, npm pack --dry-run; was 188kB incl. 44 maps referencing unshipped src) - Streamable HTTP actually wired behind RVAGENT_HTTP_PORT: one transport + one MCP server per session (mcp-session-id routing), 1MiB body cap (413), port-aware localhost origin gate; dual-transport description now true - tools renamed underscore-canonical with dotted router-only aliases - single Zod validation gate; advertised inputSchema generated from the same Zod source (zod-to-json-schema) - train_count: parent log fds closed (was leaking 2/job); job records persisted to <jobsDir>/<id>.json (job_status survives restarts); bounded log-tail reads - detectCogBinary probes its candidates instead of dead-coding them - version from package.json; @types/express dropped; @types/jest -> 29 - README rewritten to match reality (no phantom subcommands/policy layer) - 99/99 jest tests (incl. new session/body-cap suite + previously-broken manifest suite); stdio handshake + HTTP session flow smoke-tested live ADR-265 D1-D4: - .github/workflows/npm-packages.yml: 3-package x Node 20/22 gate — tests, version-literal grep (D3), pack-content/size gate, tarball-install smoke test (catches the ADR-264 F1 class), README claim-check (D4) - .github/workflows/ruview-npm-release.yml: publish from CI only with npm publish --provenance - @ruv/ruview-cli bin renamed ruview-cli (ruview bin belongs to @ruvnet/ruview); version single-sourced - ci.yml NODE_VERSION 18 -> 20 ADR statuses updated to Accepted/implemented; harness manifest re-pinned; ADR-263/264/265 + both package READMEs pass claim-check. Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01WrGfTGKv1oWZ6iwXZACULz
34 lines
1.5 KiB
Markdown
34 lines
1.5 KiB
Markdown
---
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name: train-pose
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description: Train/evaluate WiFi pose models honestly — camera-supervised (MediaPipe + CSI) and camera-free (WiFlow), always checked against the mean-pose baseline before any PCK is quoted.
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---
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# train-pose
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Build a CSI→pose model without overstating it. The project has a **retracted 92.9%/100%**
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history — the discipline below exists so it never recurs.
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## The non-negotiable: mean-pose baseline first
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A pose model that always predicts the dataset's *mean pose* already scores ~50% PCK.
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**Quote PCK only as a delta over that baseline**, on a held-out split with no subject
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or temporal leakage. Example honest result (ADR-181):
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> Held-out PCK@20 **59.5%** vs a 50% mean-pose baseline = **+9.4 pp real signal** — MEASURED.
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## Paths
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- **camera-supervised** (ADR-079) — MediaPipe Pose labels the camera frame; paired CSI
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trains the net. Train/infer in one camera frame so the skeleton aligns.
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- **camera-free** (WiFlow, ADR-152) — no camera at inference; geometry-conditioned.
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- **in-browser** (ADR-181) — WebGPU/WASM trainer; the active backend is shown as a badge
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(honest about what's executing).
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## Before you publish a number
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1. Run the mean-pose baseline on the same split.
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2. Report `(model − baseline)` in pp, with the split definition (chronological /
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blocked-gap / grouped-bucket; no leakage).
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3. `ruview_claim_check` the writeup — it flags any untagged or 100%/perfect claim.
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4. If it's a benchmark vs SOTA, tag MEASURED-EQUIVALENT only with the reproducer.
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