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docs(readme): add Claude Code / Codex plugin + marketplace install instructions 

New "🧩 Claude Code & Codex Plugin" section in README.md covering
`claude --plugin-dir`, `claude plugin marketplace add` / `install`, the seven
/ruview-* commands, the Codex prompt mirror, and the smoke check; plus a
Documentation-table row linking to plugins/ruview/README.md.

Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv 2026-05-11 19:02:05 -04:00
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@ -485,12 +485,41 @@ See [`docs/adr/ADR-024-contrastive-csi-embedding-model.md`](docs/adr/ADR-024-con
--- ---
## 🧩 Claude Code & Codex Plugin
RuView ships a [Claude Code](https://docs.anthropic.com/en/docs/claude-code) plugin (and Codex prompt mirror) that wraps the whole workflow — onboarding, ESP32 setup, configuration, sensing apps, model training, advanced multistatic sensing, CLI/API/WASM, mmWave radar, and witness verification — as 9 skills, 7 `/ruview-*` commands, and 3 agents. It lives in [`plugins/ruview/`](plugins/ruview/README.md); the marketplace manifest is [`plugins/.claude-plugin/marketplace.json`](plugins/.claude-plugin/marketplace.json).
```bash
# Try it for one session, no install:
claude --plugin-dir ./plugins/ruview
# Or add the marketplace and install:
claude plugin marketplace add ./plugins
claude plugin install ruview@ruview
# Then, in Claude Code:
# /ruview-start → onboarding (Docker demo / repo build / live ESP32)
# /ruview-flash → build + flash ESP32 firmware
# /ruview-provision → provision WiFi creds, sink IP, channel/MAC, mesh slots
# /ruview-app → run a sensing application (presence / vitals / pose / sleep / MAT / point cloud)
# /ruview-train → train / evaluate / publish a model (incl. GPU on GCloud)
# /ruview-advanced → multistatic / tomography / cross-viewpoint / mesh-security
# /ruview-verify → tests + deterministic proof + witness bundle
```
**Codex (OpenAI CLI):** `cp plugins/ruview/codex/prompts/*.md ~/.codex/prompts/` — the seven `/ruview-*` commands are mirrored as Codex prompts; [`plugins/ruview/codex/AGENTS.md`](plugins/ruview/codex/AGENTS.md) carries the project rules. See [`plugins/ruview/codex/README.md`](plugins/ruview/codex/README.md).
Verify the plugin structure: `bash plugins/ruview/scripts/smoke.sh`. Full details: [`plugins/ruview/README.md`](plugins/ruview/README.md).
---
## 📖 Documentation ## 📖 Documentation
| Document | Description | | Document | Description |
|----------|-------------| |----------|-------------|
| [User Guide](docs/user-guide.md) | Step-by-step guide: installation, first run, API usage, hardware setup, training | | [User Guide](docs/user-guide.md) | Step-by-step guide: installation, first run, API usage, hardware setup, training |
| [Build Guide](docs/build-guide.md) | Building from source (Rust and Python) | | [Build Guide](docs/build-guide.md) | Building from source (Rust and Python) |
| [Claude Code / Codex Plugin](plugins/ruview/README.md) | The `ruview` plugin + marketplace — skills, `/ruview-*` commands, agents, and the Codex prompt mirror |
| [Architecture Decisions](docs/adr/README.md) | 79 ADRs — why each technical choice was made, organized by domain (hardware, signal processing, ML, platform, infrastructure) | | [Architecture Decisions](docs/adr/README.md) | 79 ADRs — why each technical choice was made, organized by domain (hardware, signal processing, ML, platform, infrastructure) |
| [Domain Models](docs/ddd/README.md) | 7 DDD models (RuvSense, Signal Processing, Training Pipeline, Hardware Platform, Sensing Server, WiFi-Mat, CHCI) — bounded contexts, aggregates, domain events, and ubiquitous language | | [Domain Models](docs/ddd/README.md) | 7 DDD models (RuvSense, Signal Processing, Training Pipeline, Hardware Platform, Sensing Server, WiFi-Mat, CHCI) — bounded contexts, aggregates, domain events, and ubiquitous language |
| [Desktop App](v2/crates/wifi-densepose-desktop/README.md) | **WIP** — Tauri v2 desktop app for node management, OTA updates, WASM deployment, and mesh visualization | | [Desktop App](v2/crates/wifi-densepose-desktop/README.md) | **WIP** — Tauri v2 desktop app for node management, OTA updates, WASM deployment, and mesh visualization |