Intelligence Collection Methodology
RightNow-AI/openfang
Reference knowledge for open-source intelligence collection: the collection cycle, source reliability tiers, search query patterns and entity extraction.
Reference for RuView's research-grade WiFi sensing features: multistatic fusion, cross-viewpoint geometry, persistent field models, RF tomography, intention signals and mesh security.
Install RuView Advanced Sensing
$ npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ruvnet/RuView ruview-advanced-sensing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ruvnet/RuView.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ruview/skills/ruview-advanced-sensing .claude/skills/ruview-advanced-sensing && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ruview-advanced-sensing" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-advanced-sensing into .claude/skills/ruview-advanced-sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-advanced-sensing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-advanced-sensingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ruvnet/RuView ruview-advanced-sensing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/RuView.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/ruview/skills/ruview-advanced-sensing .agents/skills/ruview-advanced-sensing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ruview-advanced-sensing" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-advanced-sensing into .agents/skills/ruview-advanced-sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-advanced-sensing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ruvnet/RuView ruview-advanced-sensing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/RuView.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/ruview/skills/ruview-advanced-sensing .cursor/skills/ruview-advanced-sensing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ruview-advanced-sensing" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-advanced-sensing into .cursor/skills/ruview-advanced-sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-advanced-sensing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ruvnet/RuView.git --path plugins/ruview/skills/ruview-advanced-sensing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ruvnet/RuView ruview-advanced-sensing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/RuView.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/ruview/skills/ruview-advanced-sensing .gemini/skills/ruview-advanced-sensing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ruview-advanced-sensing" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-advanced-sensing into .gemini/skills/ruview-advanced-sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-advanced-sensing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ruvnet/RuView ruview-advanced-sensingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ruvnet/RuView.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/ruview/skills/ruview-advanced-sensing .github/skills/ruview-advanced-sensing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ruview-advanced-sensing" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-advanced-sensing into .github/skills/ruview-advanced-sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-advanced-sensing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ruvnet/RuView ruview-advanced-sensing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ruvnet/RuView.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/ruview/skills/ruview-advanced-sensing .opencode/skills/ruview-advanced-sensing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ruview-advanced-sensing" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-advanced-sensing into .opencode/skills/ruview-advanced-sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-advanced-sensing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ruview-advanced-sensing- GitHub stars
- 97k
- Token cost
- ~1.2k tokens
- SKILL.md length
- 398 words
- Files
- 1
- Skills in repo
- 24
- Repo updated
- First seen
- Licence
- MIT
At a glance
Reference for RuView's research-grade WiFi sensing features: multistatic fusion, cross-viewpoint geometry, persistent field models, RF tomography, intention signals and mesh security.
- Planning a multi-node WiFi sensing deployment
- SKILL.md covers RuvSense multistatic mode…, Cross-viewpoint fusion…, Persistent field model (ADR-030) and RF tomography, plus 4 more sections
- Calls cargo, node and python
- Working out how cross-viewpoint fusion improves localization
What it does
The deep end of the RuView project is covered here, for research-grade or multi-node deployments. RuvSense multistatic mode treats every WiFi link in range, including neighbors' access points, as a bistatic radar pair and fuses them. A table maps the 14 modules under the ruvsense folder to their roles, from multiband channel-state fusion and phase alignment to coherence gating, a 17-keypoint pose tracker, tomography, gesture classification and adversarial detection.
Cross-viewpoint fusion combines two or more nodes geometrically, with 5 modules for attention, geometric diversity, coherence and fusion, so more nodes give tighter localization. The persistent field model builds an SVD eigenstructure of the room and stores it, so new CSI frames are projected against it and the residual shows what differs from the empty-room baseline, even after restarts. Further topics are RF tomography with an ISTA L1 solver and voxel grids, longitudinal biomechanics drift, pre-movement intention signals and adversarial signal detection.
Host-side scripts such as mesh-graph-transformer.js, passive-radar.js and deep-scan.js let you explore the geometry before deploying, and the skill is allowed to use shell, file read, write and edit, and search tools.
When your agent uses it
- Planning a multi-node WiFi sensing deployment
- Working out how cross-viewpoint fusion improves localization
- Building a persistent room baseline to detect changes
- Reviewing security measures for a multistatic mesh
Example prompts
- “Explain how RuvSense fuses WiFi links into one multistatic estimate.”
- “Which modules handle RF tomography, and what solver do they use?”
- “Walk me through setting up a persistent field model for an empty room.”
- “How do I run the passive radar script to study node geometry before deploying?”
Requirements
- The RuView repository with its sensing modules and helper scripts
- Pre-approved tools (allowed-tools): Bash, Read, Write, Edit, Glob, Grep
What it can do on your machine
Read from SKILL.md and the folder at commit 0ef6b96. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
BashReadWriteEditGlobGrep
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
cargonodepython
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
RuView Advanced Sensing loads about 1.2k tokens when it runs. Until then it costs about 109 tokens; SKILL.md has 398 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Bash, Read, Write, Edit, Glob, Grep
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from ruvnet/RuView at commit 0ef6b96, republished under its MIT licence (© ruvnet). 398 words, ~1,181 tokens.
Download SKILL.mdSave it as
.claude/skills/ruview-advanced-sensing/SKILL.md (or your agent's skills folder).- name
- ruview-advanced-sensing
- description
- Advanced RuView capabilities — RuvSense multistatic sensing (attention-weighted fusion, geometric diversity, persistent field model), cross-viewpoint fusion across multiple nodes, RF tomography (ISTA L1 solver, voxel grids), longitudinal biomechanics drift, pre-movement intention signals, adversarial signal detection, and multistatic mesh security hardening. Use for research-grade or multi-node deployments.
- allowed-tools
- Bash, Read, Write, Edit, Glob, Grep
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.
Persistent field model (ADR-030)
field_model.rs builds an SVD eigenstructure of the room and stores it (RVF, ideally on a Cognitum Seed). New CSI frames are projected against it; the residual is the perturbation. Lets you ask "what's different from the empty-room baseline?" and survive restarts.
Show full SKILL.md (162 more words)Show less
RF tomography
tomography.rs reconstructs a voxel occupancy grid from the multistatic link set via an ISTA L1 solver (sparse — most voxels are empty). Use with cross-viewpoint geometry for through-wall volumetric imaging. RuVector solver crates back the sparse interpolation (114→56 subcarriers).
Sensing-first RF mode & adaptive mesh kernel
- ADR-031 (RuView sensing-first RF mode), ADR-081 (adaptive CSI mesh firmware kernel), ADR-083 (per-cluster π compute hop), ADR-095/096 (on-ESP32 temporal modeling with sparse GQA attention — runs the temporal head on-device).
Security (ADR-032 — multistatic mesh hardening)
Using neighbours' APs as illuminators and pooling links across a mesh expands the attack surface. Mitigations:
adversarial.rsrejects physically impossible signals and cross-checks multi-link consistency.coherence_gate.rsquarantines low-coherence / suspicious links (Reject / Recalibrate).- Ed25519 witness chain (ADR-028) attests every measurement.
- Run a security review when touching anything on the hardware/network boundary (see
ruview-verifyanddocs/security-audit-wasm-edge-vendor.md).
Validate advanced changes
cd v2 && cargo test --workspace --no-default-features # incl. ruvsense + viewpoint tests
cargo test -p wifi-densepose-signal --no-default-features
cargo test -p wifi-densepose-ruvector --no-default-features
cd .. && python archive/v1/data/proof/verify.pyReference
- ADRs: 014 (SOTA signal processing), 029 (multistatic mode), 030 (persistent field model), 031 (sensing-first RF), 032 (mesh security hardening), 081/083/095/096
v2/crates/wifi-densepose-signal/src/ruvsense/·v2/crates/wifi-densepose-ruvector/src/viewpoint/docs/research/,docs/security-audit-wasm-edge-vendor.md
© ruvnet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in plugins/ruview/skills/ruview-advanced-sensing of ruvnet/RuView.
Open the folder on GitHubat commit 0ef6b96
Compare with similar skills
RuView Advanced Sensing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| RuView Advanced Sensing this skillruvnet/RuView | 97k | — | ~1.2k | Automated safety check: Notes | MIT | |
| Intelligence Collection MethodologyRightNow-AI/openfang | 18k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Interceptor ResearchHacker-Valley-Media/Interceptor | 519 | — | ~3.8k | Automated safety check: Pass | Custom licence | |
| Nemo GuardrailsOrchestra-Research/AI-Research-SKILLs | 13k | 2 repos | ~1.9k | Automated safety check: Warn | MIT | |
| Bio Atac Seq FootprintingGPTomics/bioSkills | 1.2k | 2 repos | ~4.8k | Automated safety check: Pass | MIT | |
| Network And Distributed System Security Symposiumfranklee16/academic-research-skills | 223 | 1 repos | ~1.9k | Automated safety check: Pass | None |
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More from ruvnet/RuView
All 24 skills in this repoRuView Sensing Applications
ruvnet/RuView
Runs RuView's WiFi sensing applications: presence, vital signs, activity and fall detection, pose estimation, sleep monitoring and environment mapping.
RuView CLI, API and WASM
ruvnet/RuView
Covers the RuView `wifi-densepose` command line binary, its Axum REST API and the WebAssembly builds for browsers and ESP32, for embedding or scripting RuView.
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Tunes a deployed RuView WiFi-sensing system without changing code: firmware sdkconfig variants, NVS provisioning over serial, channel and MAC filtering, edge processing tiers and mesh slotting.
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Drives a web browser through the agent-browser CLI, using compact accessibility snapshots with element refs in place of the full DOM to keep context small.
RuView Hardware Setup
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Brings a RuView CSI sensing node online by building ESP32-S3 or ESP32-C6 firmware, flashing the board, provisioning WiFi and checking the serial output.
RuView mmWave Radar Setup
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Sets up and runs 60 GHz and 24 GHz mmWave radar sensing on ESP32 boards in RuView, alone or fused with WiFi CSI.
Related
Categories
Questions about RuView Advanced Sensing
What does RuView Advanced Sensing do?
Reference for RuView's research-grade WiFi sensing features: multistatic fusion, cross-viewpoint geometry, persistent field models, RF tomography, intention signals and mesh security. The deep end of the RuView project is covered here, for research-grade or multi-node deployments. RuvSense multistatic mode treats every WiFi link in range, including neighbors' access points, as a bistatic radar pair and fuses them.
When should I use RuView Advanced Sensing?
RuView Advanced Sensing fits situations like: planning a multi-node WiFi sensing deployment; working out how cross-viewpoint fusion improves localization; building a persistent room baseline to detect changes; reviewing security measures for a multistatic mesh.
How do I install RuView Advanced Sensing in Claude Code?
Run `npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a claude-code`. Or copy the skill folder (plugins/ruview/skills/ruview-advanced-sensing in ruvnet/RuView) into .claude/skills/ruview-advanced-sensing in your project. Claude Code loads it when a task matches its description.
How do I install RuView Advanced Sensing in Codex?
Run `npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a codex`. Or copy the skill folder (plugins/ruview/skills/ruview-advanced-sensing in ruvnet/RuView) into .agents/skills/ruview-advanced-sensing in your project. Codex loads it when a task matches its description.
Can I use RuView Advanced Sensing in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ruvnet/RuView --skill ruview-advanced-sensing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ruview-advanced-sensing, .gemini/skills/ruview-advanced-sensing, .github/skills/ruview-advanced-sensing and .opencode/skills/ruview-advanced-sensing in your project.
What does RuView Advanced Sensing need to run?
Going by SKILL.md and its folder, RuView Advanced Sensing needs the command-line tools its instructions call (cargo, node and python). Our summary lists: The RuView repository with its sensing modules and helper scripts. Its frontmatter pre-approves these tools: Bash, Read, Write, Edit, Glob, Grep.
Does RuView Advanced Sensing access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is RuView Advanced Sensing safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does RuView Advanced Sensing use?
RuView Advanced Sensing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does RuView Advanced Sensing use?
About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to RuView Advanced Sensing?
Skills that share tags, products or a category with RuView Advanced Sensing: Intelligence Collection Methodology (RightNow-AI/openfang, 18k stars), Interceptor Research (Hacker-Valley-Media/Interceptor, 519 stars), Nemo Guardrails (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Bio Atac Seq Footprinting (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains RuView Advanced Sensing?
ruvnet (a GitHub user) maintains it in ruvnet/RuView, which has 96,981 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 9, 2026.
Source: ruvnet/RuView on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.