Skip to content
cccskills
FreePublished on GitHub

device-access

Inspect RuView sensing hardware, including ESP32 nodes, mmWave radars, and LiDAR distance sensors. Find connected devices, read logs and live measurements, and use SSH to access supported read-only tools on another machine.

OriginalShow the original description

Reach RuView sensing hardware from the machine it is attached to — ESP32 CSI nodes (serial + UDP stream), 60 GHz MR60BHA2 / 24 GHz LD2410 mmWave radars, RPLIDAR and iPhone LiDAR — and from other machines over SSH, read-only.

See how to install

Good for

  • Finding sensing devices connected to a computer
  • Checking CSI streams and serial logs
  • Reading radar and LiDAR measurements
  • Inspecting hardware on another machine over SSH

Files included (1)

  • SKILL.md2.9 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

device-access

Hardware tools must run on the host the device is plugged into. A cloud agent cannot see your USB ports. Run npx @ruvnet/ruview locally, start a local Claude Code session there (claude remote-control in the repo if you want to drive it from the Claude app), or add the machine as an SSH host.

1. Find devices

npx @ruvnet/ruview doctor --group python,serial,devices,remote
npx @ruvnet/ruview devices          # USB VID:PID → likely ESP32 / mmWave / RPLIDAR + confirm command

2. Read each modality

DeviceCommandConfirms
ESP32 node (USB)ruview doctor --port <p> --probe, ruview monitor --port <p>chip id; CSI callbacks in the serial log (the monitor never resets the node; C6/S3 USB-Serial/JTAG builds log on the native USB port)
ESP32 / Realtek node (network)ruview esp32 --seconds 10 [--udp-port 5005]per-node CSI rate, sequence loss, RSSI, CSI shapes, device vitals; Realtek RAC1 CSI and heartbeat-only senders
Realtek RTL8721Dx (USB, PL2303)ruview monitor --port <p> --baud 1500000RUVIEW_CSI: frame # lines in the Ameba log
Live CSI → kernelruview esp32 --seconds 45 --analyze [--node-id N] [--backend napi]kernel vitals summary at the measured frame rate (no reference measurement)
60 GHz MR60BHA2ruview mmwave --port <p> --model mr60bha2valid frames, checksum errors, presence/distance/device HR+BR
24 GHz LD2410ruview mmwave --port <p> --model ld2410target state and distances
RPLIDARruview lidar --source rplidar --port <p> [--baud 115200]points, revolutions, range, angular coverage
iPhone LiDARexport RUVIEW_LIDAR_TOKEN=…; ruview lidar --source iphone --url ws://HOST:8787/ws/lidardepth frame rate, confident fraction, median depth

The UDP capture cannot share port 5005 with a running sensing server; stop the server or have the nodes target another port.

3. Other machines (SSH, read-only)

npx @ruvnet/ruview hosts add --name lab-pi --ssh ruv@lab-pi.local
ssh ruv@lab-pi.local true                       # pin the host key once
npx @ruvnet/ruview hosts run --host lab-pi --tool ruview_devices_scan
npx @ruvnet/ruview hosts run --host lab-pi --tool ruview_mmwave_read --args-json '{"port":"/dev/ttyUSB0"}'

Remote hosts run a pinned @ruvnet/ruview and accept only read-only tools. Flash, train, and calibrate on the host itself.

Evidence

Device readouts are MEASURED readings, not accuracy results. mmWave heart/breathing values are the radar's own estimates. Hardware validation still means a captured log or stream from real silicon, recorded with the command that produced it.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Build advanced AgentDB workflows with database synchronization, multiple databases, and search that combines meaning with attribute filters. Covers similarity measures, diverse search results, and operational patterns for distributed AI applications.

  • Sharing stored patterns across multiple AgentDB instances
  • Filtering semantic search by date or category
  • Separating knowledge and conversation databases
ruvnet/RuView98.8KUpdated Oct 19, 2026

Create AgentDB learning plugins that use recorded experience to improve agent decisions. Choose a learning method, store states, actions, and rewards, train models, and evaluate suggested actions through CLI and API workflows.

  • Train agents from historical experience
  • Build decision-making for games and navigation
  • Combine experience from multiple agents for training
ruvnet/RuView98.8KUpdated Oct 19, 2026

Build AI agents that retain conversation history, user preferences, and useful interaction patterns with AgentDB. The skill covers persistent storage, meaning memories survive between sessions, plus retrieval, context management, and ReasoningBank integration.

  • Add conversation history to a chat system
  • Remember user preferences across sessions
  • Reuse patterns from successful interactions
ruvnet/RuView98.8KUpdated Oct 19, 2026

Tune AgentDB memory use and search speed through quantization, which stores vectors more compactly, search indexes, caching, and batch operations. Includes configuration examples and benchmarks to help balance accuracy, speed, and storage as datasets grow.

  • Reduce memory use in an AgentDB application
  • Tune search speed while preserving accuracy
  • Plan settings for millions of vectors
ruvnet/RuView98.8KUpdated Oct 19, 2026

Build document search with AgentDB that finds related content by meaning. Store documents as numerical representations, combine similarity search with metadata filters, and retrieve relevant passages for systems that generate answers using source material.

  • Build answers grounded in retrieved documents
  • Add meaning-based search to a knowledge base
  • Find documents with similar content
ruvnet/RuView98.8KUpdated Oct 19, 2026

browser

FreeSummary

Automate browser tasks with agent-browser, using snapshots that label page elements for the agent. Handle login flows, fill and submit forms, extract page information, and capture screenshots through a repeatable navigation and interaction workflow.

  • Automating login flows
  • Filling and submitting web forms
  • Extracting product names, prices, and links
ruvnet/RuView98.8KUpdated Oct 19, 2026

See all skills by ruvnet

Report a problem with this skill