ruview-advanced-sensing

ruview-advanced-sensing is a skill for Claude Code from ruvnet/RuView. It costs 84 tokens per session (1,153 once invoked), scanned A, original, MIT.

A guide to advanced RuView Wi-Fi sensing across multiple access points and sensor nodes. It covers combining signals, tracking body keypoints, mapping radio changes through a room, detecting movement trends, and identifying suspicious signals.

In plain words
What is it for?
Use it to build multistatic sensing systems, fuse views from multiple nodes, create radio-based room maps, detect biomechanical drift, estimate pre-movement signals, and detect adversarial interference.
Why use it?
It helps combine data from several viewpoints when one sensor is not enough for reliable spatial information. It also provides methods for tracking changes over time and checking whether radio data should be trusted.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Not installable on its own: it runs a file from its repository that does not travel with it. Clone the repository, or install whatever ships that file. The line is cd .. && python archive/v1/data/proof/verify.py.

Part of the ruview plugin — 10 skills, 7 commands, 3 agents shipped together

About the project

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.

ruvnet/RuView · 92,510 stars · on GitHub · cognitum.one

Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add ruvnet/RuView
Claude Code
/plugin install ruview

Made for: Claude Code.

Or install ruview, the plugin that ships this one along with the rest of its 10 skills, 7 commands, 3 agents.

Wrote 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.

agentmods badge for ruview-advanced-sensing

README.md
[![agentmods](https://agentmods.dev/badge/skills/ruvnet/ruview/ruview-advanced-sensing.svg)](https://agentmods.dev/skills/ruvnet/ruview/ruview-advanced-sensing)
Your own site
<a href="https://agentmods.dev/skills/ruvnet/ruview/ruview-advanced-sensing"><img src="https://agentmods.dev/badge/skills/ruvnet/ruview/ruview-advanced-sensing.svg" alt="Measured on agentmods" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,153 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.01153
Opus 5 $0.00042 $0.00576
Sonnet 5 $0.00017 $0.00231
Haiku 4.5 $0.00008 $0.00115

Measured 2d ago against content hash ef500a308c5a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

ruview-advanced-sensing 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 2d 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.

plugins/ruview/skills/ruview-advanced-sensing/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

RuView Advanced Sensing

The deep end: multistatic mesh, tomography, persistent field models, and the security model that protects them. Most of this lives in wifi-densepose-signal/src/ruvsense/ (14 modules) and wifi-densepose-ruvector/src/viewpoint/ (5 modules).

RuvSense multistatic mode (ADR-029)

Treat every WiFi link in range — including neighbours' APs — as a bistatic radar pair, then fuse them.

Module (signal/src/ruvsense/) Purpose
multiband.rs Multi-band CSI frame fusion, cross-channel coherence
phase_align.rs Iterative LO phase-offset estimation, circular mean
multistatic.rs Attention-weighted fusion, geometric diversity
coherence.rs / coherence_gate.rs Z-score coherence scoring; Accept / PredictOnly / Reject / Recalibrate gate decisions
pose_tracker.rs 17-keypoint Kalman tracker with AETHER re-ID embeddings
field_model.rs SVD room eigenstructure, perturbation extraction
tomography.rs RF tomography, ISTA L1 solver, voxel grid
longitudinal.rs Welford stats, biomechanics drift detection
intention.rs Pre-movement lead signals (200–500 ms ahead)
cross_room.rs Environment fingerprinting, transition graph
gesture.rs DTW template-matching gesture classifier
adversarial.rs Physically-impossible-signal detection, multi-link consistency

Cross-viewpoint fusion (ADR-016 viewpoint module)

Combine 2+ nodes geometrically — more nodes, more independent looks, tighter localization.

Module (ruvector/src/viewpoint/) Purpose
attention.rs CrossViewpointAttention, GeometricBias, softmax with G_bias
geometry.rs GeometricDiversityIndex, Cramér–Rao bounds, Fisher Information
coherence.rs Phase-phasor coherence, hysteresis gate
fusion.rs MultistaticArray aggregate root, domain events

Host-side helpers to explore the geometry before deploying: node scripts/mesh-graph-transformer.js, node scripts/passive-radar.js, node scripts/deep-scan.js.

Read the full file on GitHub · 77 lines

Changes

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.

  1. 2d ago First seen · 77 lines · 84 tokens per session scan A ef500a308c5a

Subscribe to this mod's changes

ruview-advanced-sensing is a skill published in the GitHub repository ruvnet/RuView (92,510 stars, last pushed today), licensed MIT. It adds 84 tokens to every session and 1,153 once invoked, about $0.0004 per session on Opus 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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