RuView is a WiFi sensing platform that uses disturbances in radio signals, captured by low-cost ESP32 sensors, to detect presence, movement, breathing, and heart rate without cameras or wearables. It is intended for spatial monitoring and smart-home integrations. The catalogue add-ons support workflows for operating and integrating RuView.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ruvnet/RuViewnpx agentmods add skills/ruvnet/ruview/ruview-mmwaveWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ruvnet/ruview/ruview-mmwave)<a href="https://agentmods.dev/skills/ruvnet/ruview/ruview-mmwave"><img src="https://agentmods.dev/badge/skills/ruvnet/ruview/ruview-mmwave/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ruvnet/ruview/ruview-mmwave"><img src="https://agentmods.dev/badge/skills/ruvnet/ruview/ruview-mmwave.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00116 | $0.01017 |
| Opus 5.5 | $0.00046 | $0.00407 |
| Sonnet 5.5 | $0.00023 | $0.00203 |
| Haiku 4.5 | $0.00012 | $0.00102 |
Grade A, and why
ruview-mmwave scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RuView mmWave / FMCW Radar
The radio side-channel: 60 GHz and 24 GHz FMCW radar, standalone and fused with WiFi CSI.
Hardware
| Device | Port | Band | Provides | ~Cost |
|---|---|---|---|---|
| ESP32-C6 + Seeed MR60BHA2 | COM4 (typical) | 60 GHz FMCW | Heart rate, breathing rate, presence | ~$15 |
| HLK-LD2410 | — | 24 GHz FMCW | Presence + distance (gated zones) | ~$3 |
The C6 is RISC-V and can run the radar pipeline; it is not a WiFi-CSI node (use an ESP32-S3 for CSI). LD2410 is a UART module wired to a host or to the C6.
1. Firmware with mmWave fusion (v0.5.0+)
The ESP32 firmware auto-detects an attached MR60BHA2 or LD2410 and emits 48-byte fused vitals records (CSI-derived + radar-derived, reconciled). Binary is ~12 KB larger than the CSI-only build. Build/flash as in ruview-hardware-setup (Windows: Python-subprocess; ESP-IDF v5.4 ≠ Git Bash). Recommended stable firmware tag: v0.5.0-esp32 or later — see docs/user-guide.md release table.
# Provision the radar/fusion node (same provision.py; the firmware probes for the radar on boot)
python firmware/esp32-csi-node/provision.py --port COM8 --ssid "WiFi" --password "secret" --target-ip 192.168.1.20
# Confirm: serial monitor should report which radar was detected and start emitting fused vitals
2. mmWave ↔ WiFi-CSI fusion bridge (host side)
python scripts/mmwave_fusion_bridge.py # bridges radar HR/BR + CSI → unified spatial model
node scripts/passive-radar.js # passive-radar style processing for exploration
The 3D point-cloud demo fuses camera depth (MiDaS) + WiFi CSI + mmWave radar → unified spatial model (~22 ms pipeline, 19K+ pts/frame; ADR-094). Drive it with scripts/mmwave_fusion_bridge.py plus the point-cloud front-end.
3. Standalone radar use
- MR60BHA2 (60 GHz) — best for contactless vitals on a (near-)stationary subject: blood pressure proxy, heart rate, breathing rate; $15 hardware, no wearable. See
examples/medical/README.md. - LD2410 (24 GHz) — best for cheap presence + coarse distance / gated zones; complements CSI presence (PIR-style fusion) for higher confidence.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 62 lines · 116 tokens per session scan A d11b818564c3
ruview-mmwave is a skill published in the GitHub repository ruvnet/RuView (99,588 stars, last pushed today), licensed MIT. It adds 116 tokens to every session and 1,017 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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