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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>
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| description | argument-hint |
|---|---|
| Run a RuView sensing application — presence, vitals, pose, sleep, environment mapping, MAT, point cloud, or a novel RF app. | [presence|vitals|pose|sleep|environment|mat|pointcloud|<name>] |
/ruview-app
Launch a RuView application.
- Invoke the
ruview-applicationsskill. - Map
$ARGUMENTSto an application; if empty, show the catalogue and ask. Quick mappings:presence/vitals/pose/environment→cd v2 && cargo run -p wifi-densepose-sensing-server(live ESP32 sink) or the Docker demo for simulated CSI; for environment also--build-index env.sleep→examples/sleep/+node scripts/apnea-detector.js.mat(Mass Casualty Assessment) →wifi-densepose-matcrate,docs/wifi-mat-user-guide.md.pointcloud→python scripts/mmwave_fusion_bridge.py(camera depth + CSI + mmWave).- novel RF →
scripts/passive-radar.js,material-classifier.js,device-fingerprint.js,mincut-person-counter.js.
- If no hardware: fall back to
docker run -p 3000:3000 ruvnet/wifi-densepose:latestorpython examples/ruview_live.py. - Help pick the right modality (through-wall → presence/activity; stationary subject → vitals/sleep; need skeletons → pose, train it for accuracy; search & rescue → MAT; best accuracy → 2+ nodes + cross-viewpoint fusion via
/ruview-advanced).