mirror of https://github.com/ruvnet/RuView synced 2026-06-09 10:13:17 +00:00

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ruv 8ff7c2c35a feat(plugins): RuView Claude Code + Codex marketplace plugin

Add `plugins/ruview` — an end-to-end toolkit for working with RuView
(WiFi-DensePose) from Claude Code, mirrored as Codex prompts.

Marketplace: `plugins/.claude-plugin/marketplace.json` (one plugin, `ruview`).

Skills (9): ruview-quickstart, ruview-hardware-setup, ruview-configure,
ruview-applications, ruview-model-training, ruview-advanced-sensing,
ruview-cli-api, ruview-mmwave, ruview-verify — shell-first (cargo / python /
idf.py / docker / node), no claude-flow MCP dependency.

Commands (7): /ruview-start, /ruview-flash, /ruview-provision, /ruview-app,
/ruview-train, /ruview-advanced, /ruview-verify.

Agents (3): ruview-onboarding-guide, ruview-config-engineer,
ruview-training-engineer.

Codex mirror: codex/AGENTS.md + codex/README.md + codex/prompts/*.md (full
command parity, enforced by scripts/smoke.sh).

Docs: docs/adrs/0001-ruview-plugin-contract.md (Proposed). Verification:
scripts/smoke.sh (13 structural checks). Provisioning docs reflect the full
`provision.py` flag set (TDM mesh, edge tiers, vitals, hop channels, Cognitum
Seed, swarm intervals) and the issue #391 NVS-namespace-replace gotcha.

Verified: `claude plugin validate` (plugin + marketplace), loads via
`claude --plugin-dir`, smoke 13/13, and confirmed against an attached ESP32-S3
on COM8 running the RuView CSI firmware (live adaptive_ctrl + csi_collector
serial output).

Co-Authored-By: claude-flow <ruv@ruv.net>

2026-05-11 17:39:16 -04:00

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/ruview-app — run a RuView sensing application

Run a RuView application. Which one: $ARGUMENTS (one of presence, vitals, pose, sleep, environment, mat, pointcloud, or a novel-RF app name; if empty, show the catalogue and ask).

presence / vitals / pose / environment → cd v2 && cargo run -p wifi-densepose-sensing-server against a live ESP32 sink, or the Docker demo (docker run -p 3000:3000 ruvnet/wifi-densepose:latest) for simulated CSI. For environment also -- --model model.rvf --build-index env. Vitals: breathing 6–30 BPM (bandpass 0.1–0.5 Hz), heart rate 40–120 BPM (bandpass 0.8–2.0 Hz), wifi-densepose-vitals crate (ADR-021). Pose: 17 COCO keypoints via WiFlow (ADR-059 live pipeline) — train for accuracy (/ruview-train).
sleep → examples/sleep/ + node scripts/apnea-detector.js (sleep-stage classification, apnea screening).
mat (Mass Casualty Assessment — disaster survivor detection) → wifi-densepose-mat crate, docs/wifi-mat-user-guide.md.
pointcloud → python scripts/mmwave_fusion_bridge.py (camera depth via MiDaS + WiFi CSI + mmWave radar → unified spatial model, ~22 ms, 19K+ pts/frame; ADR-094).
novel RF → scripts/passive-radar.js, material-classifier.js, device-fingerprint.js, mincut-person-counter.js, gait-analyzer.js (ADR-077/078).

No hardware? Fall back to the Docker demo or python examples/ruview_live.py. Visualisers: node scripts/csi-spectrogram.js, node scripts/csi-graph-visualizer.js.

Help me pick: through-wall → presence/activity (≤5 m depth); stationary subject → vitals/sleep; need skeletons → pose (train it); search & rescue → MAT; best spatial accuracy → 2+ ESP32 nodes + cross-viewpoint fusion (v2/crates/wifi-densepose-ruvector/src/viewpoint/), optionally + Cognitum Seed. Examples: examples/{environment,medical,sleep,stress,happiness-vector}/.

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/ruview-app — run a RuView sensing application

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