Embedded Debug
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Firmware crash analysis, stack trace decoder, and register dump interpreter for ESP32/ARM/AVR platforms.
Runs RuView's WiFi sensing applications: presence, vital signs, activity and fall detection, pose estimation, sleep monitoring and environment mapping.
Install RuView Sensing Applications
$ npx skills add ruvnet/RuView --skill ruview-applications -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ruvnet/RuView ruview-applications --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-applications .claude/skills/ruview-applications && 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-applications" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-applications into .claude/skills/ruview-applications/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-applications", 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-applicationsType 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-applications -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ruvnet/RuView ruview-applications --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-applications .agents/skills/ruview-applications && 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-applications" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-applications into .agents/skills/ruview-applications/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-applications", 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-applications -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ruvnet/RuView ruview-applications --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-applications .cursor/skills/ruview-applications && 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-applications" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-applications into .cursor/skills/ruview-applications/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-applications", 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-applications--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-applications -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ruvnet/RuView ruview-applications --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-applications .gemini/skills/ruview-applications && 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-applications" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-applications into .gemini/skills/ruview-applications/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-applications", 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-applicationsInstalls 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-applications -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-applications .github/skills/ruview-applications && 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-applications" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-applications into .github/skills/ruview-applications/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-applications", 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-applications -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-applications --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-applications .opencode/skills/ruview-applications && 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-applications" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-applications into .opencode/skills/ruview-applications/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-applications", 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-applications- GitHub stars
- 97k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 334 words
- Files
- 1
- Skills in repo
- 24
- Repo updated
- First seen
- Licence
- MIT
At a glance
Runs RuView's WiFi sensing applications: presence, vital signs, activity and fall detection, pose estimation, sleep monitoring and environment mapping.
- Running presence or occupancy detection with a working RuView setup
- SKILL.md covers Application catalogue, Quick recipes, Picking the right modality and Examples directory map, plus 1 more section
- Calls cargo, node and docker
- Monitoring breathing, heart rate or sleep without contact
What it does
The skill is a catalogue of what RuView can sense from WiFi signals and how to start each application. It assumes you already have the Docker demo with simulated CSI or a live ESP32 sink, set up through companion quickstart and hardware skills. Applications include presence and occupancy, vital signs such as breathing and heart rate, activity recognition including falls, 17-keypoint pose estimation with the WiFlow architecture, sleep monitoring with apnea screening, environment mapping, Mass Casualty Assessment, an optional 3D point-cloud fusion demo and RF experiments such as passive radar.
Each row names an entry point, such as the sensing server's live mode, a crate, an examples folder or a script like gait-analyzer.js or apnea-detector.js. The quick recipes start the Docker demo on port 3000. A guide to picking the right modality suggests presence and activity for through-wall sensing with limited depth, and vitals plus sleep staging for a stationary person, with breathing first because heart rate needs a cleaner signal.
When your agent uses it
- Running presence or occupancy detection with a working RuView setup
- Monitoring breathing, heart rate or sleep without contact
- Trying pose estimation or activity and fall detection from WiFi signals
- Choosing which RuView application suits a sensing goal
Example prompts
- “Start the RuView Docker demo and show me the presence detection view.”
- “Run the sleep monitoring example and explain what it reports.”
- “Which RuView application should I use to detect someone sitting still behind a wall?”
- “Run the pose estimation demo with the sensing server.”
Requirements
- A working RuView setup: the Docker demo or a live ESP32 sink
- 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:
cargonodedockerpython
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use docker, which can reach the network depending on how they are called.
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 Sensing Applications loads about 1.1k tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 334 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). 334 words, ~1,137 tokens.
Download SKILL.mdSave it as
.claude/skills/ruview-applications/SKILL.md (or your agent's skills folder).- name
- ruview-applications
- description
- Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud fusion demo. Use when someone wants to actually *do* something with a working RuView setup.
- allowed-tools
- Bash, Read, Write, Edit, Glob, Grep
RuView Applications
What RuView can sense, and how to run each one. Assumes you have either the Docker demo (simulated CSI) or a live ESP32 sink (see ruview-quickstart / ruview-hardware-setup).
Application catalogue
| Application | What it does | Entry point |
|---|---|---|
| Presence / occupancy | Detect people through walls, count them, track entries/exits (trained model + PIR fusion, ~0.012 ms latency) | sensing-server live mode; examples/environment/ |
| Vital signs | Breathing 6–30 BPM (bandpass 0.1–0.5 Hz), heart rate 40–120 BPM (bandpass 0.8–2.0 Hz), contactless while sleeping/sitting | wifi-densepose-vitals crate (ADR-021); examples/medical/ |
| Activity recognition | Walking, sitting, gestures, falls — from temporal CSI patterns | RuvSense gesture.rs (DTW), pose_tracker.rs; scripts/gait-analyzer.js |
| Pose estimation | 17 COCO keypoints via WiFlow architecture; dual-modal webcam+WiFi fusion demo | cargo run -p wifi-densepose-sensing-server + pose-fusion demo (ADR-059); see ruview-model-training to train |
| Sleep monitoring | Overnight monitoring, sleep-stage classification, apnea screening | examples/sleep/; scripts/apnea-detector.js |
| Environment mapping | RF fingerprinting identifies rooms, detects moved furniture, spots new objects | sensing-server --build-index env; RuvSense field_model.rs, cross_room.rs |
| Mass Casualty Assessment (MAT) | Disaster survivor detection — find people in rubble/smoke | wifi-densepose-mat crate; docs/wifi-mat-user-guide.md; examples/medical/ |
| 3D point cloud (optional fusion) | Camera depth (MiDaS) + WiFi CSI + mmWave radar → unified spatial model (~22 ms, 19K+ pts/frame) | scripts/mmwave_fusion_bridge.py; ADR-094 (GitHub Pages deploy) |
| Novel RF apps | Passive radar, material classification, device fingerprinting, mincut person-counting | scripts/passive-radar.js, material-classifier.js, device-fingerprint.js, mincut-person-counter.js (ADR-077/078) |
Quick recipes
# Docker demo — everything, simulated CSI
docker run -p 3000:3000 ruvnet/wifi-densepose:latest # http://localhost:3000
# Live sensing server (consumes ESP32 UDP CSI)
cd v2 && cargo run -p wifi-densepose-sensing-server
# Live RF room scan (Cognitum Seed on :5006)
node scripts/rf-scan.js --port 5006
node scripts/snn-csi-processor.js --port 5006
# Embed a trained model + build an environment index
cd v2
cargo run -p wifi-densepose-sensing-server -- --model model.rvf --embed
cargo run -p wifi-densepose-sensing-server -- --model model.rvf --build-index env
# Python live demo
python examples/ruview_live.py
# Spectrogram / graph visualisers
node scripts/csi-spectrogram.js
node scripts/csi-graph-visualizer.jsPicking the right modality
- Through a wall, no line of sight → presence + activity; expect ≤5 m depth (Fresnel-zone geometry).
- Person stationary (sleeping / sitting) → vitals (breathing first, heart rate needs cleaner signal) + sleep staging.
- Need skeletons → pose (WiFlow). Camera-free works but is modest; camera-supervised gets 92.9% PCK@20 — train it (
ruview-model-training). - Search & rescue → MAT (
docs/wifi-mat-user-guide.md). - "What changed in this room?" → environment mapping / RF fingerprint index.
- Best spatial accuracy → 2+ ESP32 nodes + cross-viewpoint fusion (
ruview-advanced-sensing), optionally + Cognitum Seed.
Examples directory map
examples/environment/ · examples/medical/ · examples/sleep/ · examples/stress/ · examples/happiness-vector/ · examples/ruview_live.py — each has a README.
Reference
README.md— feature matrix, latency/throughput numbersdocs/user-guide.md,docs/wifi-mat-user-guide.md- ADRs: 021 (vitals), 024 (AETHER contrastive embeddings), 027 (MERIDIAN domain generalization), 041 (edge modules), 059 (live ESP32 pipeline), 077/078 (novel RF apps), 082 (pose tracker output filter), 094 (point cloud)
- RuvSense modules:
v2/crates/wifi-densepose-signal/src/ruvsense/(14 modules)
© 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-applications of ruvnet/RuView.
Open the folder on GitHubat commit 0ef6b96
Compare with similar skills
RuView Sensing Applications 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 Sensing Applications this skillruvnet/RuView | 97k | — | ~1.1k | Automated safety check: Notes | MIT | |
| Embedded DebugFastLED/FastLED | 7.5k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Scraper Builderjwynia/agent-skills | 166 | — | ~4k | Automated safety check: Pass | MIT | |
| Google Maps Lead Scrapergosom/google-maps-scraper | 6.3k | — | ~1.8k | Automated safety check: Warn | MIT | |
| Google Maps ScraperMahanaicoach/google-maps-scraper-kit | 1.3k | — | ~2.8k | Automated safety check: Pass | MIT | |
| Withings Health Data Readerwin4r/MuseAI-Skills | 332 | 2 repos | ~1.3k | Automated safety check: Pass | None |
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Related
Questions about RuView Sensing Applications
What does RuView Sensing Applications do?
Runs RuView's WiFi sensing applications: presence, vital signs, activity and fall detection, pose estimation, sleep monitoring and environment mapping. The skill is a catalogue of what RuView can sense from WiFi signals and how to start each application. It assumes you already have the Docker demo with simulated CSI or a live ESP32 sink, set up through companion quickstart and hardware skills.
When should I use RuView Sensing Applications?
RuView Sensing Applications fits situations like: running presence or occupancy detection with a working RuView setup; monitoring breathing, heart rate or sleep without contact; trying pose estimation or activity and fall detection from WiFi signals; choosing which RuView application suits a sensing goal.
How do I install RuView Sensing Applications in Claude Code?
Run `npx skills add ruvnet/RuView --skill ruview-applications -a claude-code`. Or copy the skill folder (plugins/ruview/skills/ruview-applications in ruvnet/RuView) into .claude/skills/ruview-applications in your project. Claude Code loads it when a task matches its description.
How do I install RuView Sensing Applications in Codex?
Run `npx skills add ruvnet/RuView --skill ruview-applications -a codex`. Or copy the skill folder (plugins/ruview/skills/ruview-applications in ruvnet/RuView) into .agents/skills/ruview-applications in your project. Codex loads it when a task matches its description.
Can I use RuView Sensing Applications 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-applications -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-applications, .gemini/skills/ruview-applications, .github/skills/ruview-applications and .opencode/skills/ruview-applications in your project.
What does RuView Sensing Applications need to run?
Going by SKILL.md and its folder, RuView Sensing Applications needs the command-line tools its instructions call (cargo, node, docker and python). Our summary lists: A working RuView setup: the Docker demo or a live ESP32 sink. Its frontmatter pre-approves these tools: Bash, Read, Write, Edit, Glob, Grep.
Does RuView Sensing Applications access the network?
SKILL.md contains no URLs. Its commands use docker, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is RuView Sensing Applications 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 Sensing Applications use?
RuView Sensing Applications 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 Sensing Applications use?
About 1.1k tokens (SKILL.md is roughly 4.5k 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 Sensing Applications?
Skills that share tags, products or a category with RuView Sensing Applications: Embedded Debug (FastLED/FastLED, 7.5k stars), Scraper Builder (jwynia/agent-skills, 166 stars), Google Maps Lead Scraper (gosom/google-maps-scraper, 6.3k stars) and Google Maps Scraper (Mahanaicoach/google-maps-scraper-kit, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains RuView Sensing Applications?
ruvnet (a GitHub user) maintains it in ruvnet/RuView, which has 96,839 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 8, 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.