Release
matrixorigin/memoria
Cut a Memoria release. An agent skill from matrixorigin/memoria.
Gets a newcomer to a running RuView WiFi sensing dashboard, picking between a no-hardware Docker demo, a source build or live ESP32-S3 sensing.
Install RuView Quickstart
$ npx skills add ruvnet/RuView --skill ruview-quickstart -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ruvnet/RuView ruview-quickstart --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-quickstart .claude/skills/ruview-quickstart && 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-quickstart" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-quickstart into .claude/skills/ruview-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-quickstart", 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-quickstartType 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-quickstart -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ruvnet/RuView ruview-quickstart --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-quickstart .agents/skills/ruview-quickstart && 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-quickstart" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-quickstart into .agents/skills/ruview-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-quickstart", 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-quickstart -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ruvnet/RuView ruview-quickstart --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-quickstart .cursor/skills/ruview-quickstart && 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-quickstart" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-quickstart into .cursor/skills/ruview-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-quickstart", 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-quickstart--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-quickstart -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ruvnet/RuView ruview-quickstart --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-quickstart .gemini/skills/ruview-quickstart && 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-quickstart" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-quickstart into .gemini/skills/ruview-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-quickstart", 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-quickstartInstalls 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-quickstart -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-quickstart .github/skills/ruview-quickstart && 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-quickstart" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-quickstart into .github/skills/ruview-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-quickstart", 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-quickstart -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-quickstart --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-quickstart .opencode/skills/ruview-quickstart && 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-quickstart" agent skill from https://github.com/ruvnet/RuView/tree/main/plugins/ruview/skills/ruview-quickstart into .opencode/skills/ruview-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ruview-quickstart", 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-quickstart- GitHub stars
- 97k
- Token cost
- ~794 tokens
- SKILL.md length
- 242 words
- Files
- 1
- Skills in repo
- 24
- Repo updated
- First seen
- Licence
- MIT
At a glance
Gets a newcomer to a running RuView WiFi sensing dashboard, picking between a no-hardware Docker demo, a source build or live ESP32-S3 sensing.
- Trying the RuView dashboard with no sensor hardware
- SKILL.md covers Tier 0 — Docker, no hardware…, Tier 1 — Build the repo from…, Tier 2 — Live sensing with an… and What to know before you start, plus 2 more sections
- Calls cargo, python and docker
- Building the RuView source tree and running its test suite
What it does
The skill offers three tiers matched to the hardware on hand. Tier 0 runs a Docker image with simulated data so the dashboard opens at localhost:3000 with no sensor at all. Tier 1 builds the project from source, including a Rust workspace test suite, and gives a fix for a hash-mismatch failure in verify.py after a numpy or scipy upgrade. Tier 2 is live sensing with an ESP32-S3 board, handing off to a separate hardware-setup skill for flashing and provisioning before starting the sensing server that reads its UDP data stream.
It notes that the original ESP32 and ESP32-C3 cannot run the needed signal-processing pipeline, that a single node gives limited spatial resolution so two or more are recommended, and that accuracy without a camera is modest compared with the camera-supervised training covered in a separate model-training skill. Everything runs on local hardware with no cloud service required. A table points to further skills for configuration, sensing applications, model training, advanced multi-node sensing and build verification.
When your agent uses it
- Trying the RuView dashboard with no sensor hardware
- Building the RuView source tree and running its test suite
- Setting up live WiFi sensing with an ESP32-S3 board
Example prompts
- “Run the RuView Docker demo so I can see the dashboard with simulated data.”
- “Build the v2 workspace from source and run its test suite.”
- “I have an ESP32-S3, walk me through getting live sensing running.”
Requirements
- Docker for the no-hardware demo
- A Rust toolchain for building from source
- An ESP32-S3 or ESP32-C6 board for live sensing
- 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:
cargopythondockernode
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 Quickstart loads about 794 tokens when it runs. Until then it costs about 64 tokens; SKILL.md has 242 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). 242 words, ~794 tokens.
Download SKILL.mdSave it as
.claude/skills/ruview-quickstart/SKILL.md (or your agent's skills folder).- name
- ruview-quickstart
- description
- Onboarding and first-run for RuView (WiFi-DensePose) — Docker demo with simulated data, repo build, and the fastest path to a live sensing dashboard. Use when someone is new to RuView or wants the shortest path to "it works on my machine".
- allowed-tools
- Bash, Read, Write, Edit, Glob, Grep
RuView Quickstart
Get a newcomer from zero to a running RuView sensing dashboard. Three tiers, pick the one that matches the hardware on hand.
Tier 0 — Docker, no hardware (2 minutes)
docker pull ruvnet/wifi-densepose:latest
docker run -p 3000:3000 ruvnet/wifi-densepose:latest
# open http://localhost:3000 — simulated CSI, full UIUse this to demo the dashboard, explore the API, or develop UI without a sensor.
Tier 1 — Build the repo from source
# Rust workspace (1,400+ tests, ~2 min)
cd v2
cargo test --workspace --no-default-features
# Single-crate sanity check (no GPU)
cargo check -p wifi-densepose-train --no-default-features
# Python proof (deterministic SHA-256 pipeline check)
cd ..
python archive/v1/data/proof/verify.py # must print VERDICT: PASSIf verify.py fails on a hash mismatch after a numpy/scipy bump:
python archive/v1/data/proof/verify.py --generate-hash
python archive/v1/data/proof/verify.pyTier 2 — Live sensing with an ESP32-S3 ($9)
This is the real thing. Hand off to the ruview-hardware-setup skill for the flash/provision/monitor loop, then:
# Lightweight sensing server (consumes the ESP32 UDP CSI stream)
cd v2
cargo run -p wifi-densepose-sensing-server
# Live RF room scan / SNN learning helpers:
node ../scripts/rf-scan.js --port 5006
node ../scripts/snn-csi-processor.js --port 5006What to know before you start
- ESP32-C3 and the original ESP32 are NOT supported — single-core, can't run the CSI DSP pipeline. Use ESP32-S3 (8MB or 4MB) or ESP32-C6.
- A single ESP32 has limited spatial resolution — 2+ nodes (or add a Cognitum Seed) for good results.
- Camera-free pose accuracy is limited (~84s to train, modest PCK). For 92.9% PCK@20 use camera-supervised training (see
ruview-model-trainingskill, ADR-079). - No cloud, no internet, no cameras required — everything runs on edge hardware.
Next steps to suggest
| Goal | Skill / command |
|---|---|
| Flash & provision an ESP32 node | ruview-hardware-setup · /ruview-flash · /ruview-provision |
| Tune channels / MAC filter / edge modules | ruview-configure |
| Run a sensing application (presence, vitals, pose, sleep, MAT) | ruview-applications · /ruview-app |
| Train a pose / sensing model | ruview-model-training · /ruview-train |
| Multistatic mesh, tomography, cross-viewpoint fusion | ruview-advanced-sensing · /ruview-advanced |
| Verify the build + generate a witness bundle | ruview-verify · /ruview-verify |
Reference
README.md— feature matrix, hardware table, install optionsdocs/user-guide.md,docs/wifi-mat-user-guide.md,docs/build-guide.md,docs/TROUBLESHOOTING.mddocs/tutorials/,examples/— runnable examples (environment, medical, sleep, stress,ruview_live.py)
© 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-quickstart of ruvnet/RuView.
Open the folder on GitHubat commit 0ef6b96
Compare with similar skills
RuView Quickstart 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 Quickstart this skillruvnet/RuView | 97k | — | ~794 | Automated safety check: Notes | MIT | |
| Releasematrixorigin/memoria | 607 | — | ~494 | Automated safety check: Pass | Apache-2.0 | |
| Ros2 Engineering SkillsLeoYeAI/openclaw-master-skills | 2.2k | — | ~5k | Automated safety check: Notes | MIT | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| GitHub Actions CreatorFNOSP/FlyNarwhal | 495 | 1 repos | ~2.4k | Automated safety check: Pass | AGPL-3.0 | |
| Tsk Configdtormoen/tsk-tsk | 171 | — | ~2.8k | Automated safety check: Notes | MIT |
Similar skills
Ros2 Engineering Skills
LeoYeAI/openclaw-master-skills
Comprehensive ROS 2 engineering guide covering workspace setup, node architecture, communication patterns (topics/services/actions with QoS), lifecycle and component nodes, launch composition…
GreptimeDB Dev Docker Image
GreptimeTeam/greptimedb
Packages a locally built GreptimeDB debug binary into a development-only Docker image for local-cluster testing, with an optional push to a dev registry.
GitHub Actions Creator
FNOSP/FlyNarwhal
A skill your agent uses when the user wants to create, generate, or set up a GitHub Actions workflow.
Tsk Config
dtormoen/tsk-tsk
A skill your agent uses when the user wants to set up or configure tsk Docker container images, customize their tsk.toml for Docker builds, configure stack/agent/project layers, or troubleshoot tsk…
Frb Docker
fzyzcjy/flutter_rust_bridge
A skill your agent uses for ordinary flutterrustbridge Docker/devcontainer setup, local image usage, and Apple Silicon containers; route image upgrades and publishing to frb-upgrade-docker.
More from ruvnet/RuView
All 24 skills in this repoRuView Advanced Sensing
ruvnet/RuView
Reference for RuView's research-grade WiFi sensing features: multistatic fusion, cross-viewpoint geometry, persistent field models, RF tomography, intention signals and mesh security.
RuView 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.
RuView Deployment Configuration
ruvnet/RuView
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.
Agent-Browser Automation
ruvnet/RuView
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
ruvnet/RuView
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.
Related
Categories
Questions about RuView Quickstart
What does RuView Quickstart do?
Gets a newcomer to a running RuView WiFi sensing dashboard, picking between a no-hardware Docker demo, a source build or live ESP32-S3 sensing. The skill offers three tiers matched to the hardware on hand. Tier 0 runs a Docker image with simulated data so the dashboard opens at localhost:3000 with no sensor at all.
When should I use RuView Quickstart?
RuView Quickstart fits situations like: trying the RuView dashboard with no sensor hardware; building the RuView source tree and running its test suite; setting up live WiFi sensing with an ESP32-S3 board.
How do I install RuView Quickstart in Claude Code?
Run `npx skills add ruvnet/RuView --skill ruview-quickstart -a claude-code`. Or copy the skill folder (plugins/ruview/skills/ruview-quickstart in ruvnet/RuView) into .claude/skills/ruview-quickstart in your project. Claude Code loads it when a task matches its description.
How do I install RuView Quickstart in Codex?
Run `npx skills add ruvnet/RuView --skill ruview-quickstart -a codex`. Or copy the skill folder (plugins/ruview/skills/ruview-quickstart in ruvnet/RuView) into .agents/skills/ruview-quickstart in your project. Codex loads it when a task matches its description.
Can I use RuView Quickstart 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-quickstart -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-quickstart, .gemini/skills/ruview-quickstart, .github/skills/ruview-quickstart and .opencode/skills/ruview-quickstart in your project.
What does RuView Quickstart need to run?
Going by SKILL.md and its folder, RuView Quickstart needs the command-line tools its instructions call (cargo, python, docker and node). Our summary lists: Docker for the no-hardware demo; A Rust toolchain for building from source; An ESP32-S3 or ESP32-C6 board for live sensing. Its frontmatter pre-approves these tools: Bash, Read, Write, Edit, Glob, Grep.
Does RuView Quickstart 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 Quickstart 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 Quickstart use?
RuView Quickstart 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 Quickstart use?
About 794 tokens (SKILL.md is roughly 3.2k 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 Quickstart?
Skills that share tags, products or a category with RuView Quickstart: Release (matrixorigin/memoria, 607 stars), Ros2 Engineering Skills (LeoYeAI/openclaw-master-skills, 2.2k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars) and GitHub Actions Creator (FNOSP/FlyNarwhal, 495 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains RuView Quickstart?
ruvnet (a GitHub user) maintains it in ruvnet/RuView, which has 96,741 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 7, 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.