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anthropics/skills
Builds multi-component claude.ai HTML artifacts as a small React, TypeScript and Tailwind project, then bundles it into one shareable HTML file.
React to passive device events tagged [sensing:...] — presence, sound, light, fire hazard — with inline emotion markers and optional short speech.
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill sensing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System 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/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/sensing .claude/skills/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 "sensing" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/sensing into .claude/skills/sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/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 autonomous-ai/Physical-AI-Operating-System --skill sensing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System sensing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/sensing .agents/skills/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 "sensing" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/sensing into .agents/skills/sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 autonomous-ai/Physical-AI-Operating-System --skill sensing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System sensing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/sensing .cursor/skills/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 "sensing" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/sensing into .cursor/skills/sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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/autonomous-ai/Physical-AI-Operating-System.git --path skills/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 autonomous-ai/Physical-AI-Operating-System --skill sensing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install autonomous-ai/Physical-AI-Operating-System sensing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/sensing .gemini/skills/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 "sensing" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/sensing into .gemini/skills/sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 autonomous-ai/Physical-AI-Operating-System 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 autonomous-ai/Physical-AI-Operating-System --skill sensing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/sensing .github/skills/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 "sensing" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/sensing into .github/skills/sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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 autonomous-ai/Physical-AI-Operating-System --skill 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 autonomous-ai/Physical-AI-Operating-System sensing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autonomous-ai/Physical-AI-Operating-System.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/sensing .opencode/skills/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 "sensing" agent skill from https://github.com/autonomous-ai/Physical-AI-Operating-System/tree/main/skills/sensing into .opencode/skills/sensing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "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.
sensingReact to passive device events tagged [sensing:...] — presence, sound, light, fire hazard — with inline emotion markers and optional short speech.
Sensing is an agent skill from autonomous-ai/Physical-AI-Operating-System. React to passive device events tagged [sensing:...] — presence, sound, light, fire hazard — with inline emotion markers and optional short speech. Does NOT handle motion.activity (→ wellbeing) or emotion.detected / speechemotion.detected (→ user-emotion-detection).
Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.json`).
It works with React. The repository describes itself as: The open-source operating system for physical AI. The licence is Apache-2.0.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit f1b9ebe. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
curlFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Sensing loads about 4.3k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 2,149 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.
The automated check found no risky patterns in SKILL.md.
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.
The full file from autonomous-ai/Physical-AI-Operating-System at commit f1b9ebe, republished under its Apache-2.0 licence (© autonomous-ai). 2,149 words, ~4,281 tokens.
.claude/skills/sensing/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.[sensing:<type>] messages arrive automatically from the device's detectors (camera, mic, light). Your reply goes directly to the speaker.
For events handled by this skill, output ONLY the exact [HW:...] markers from the matching row, followed by ONE sentence of at most 20 words in current_language, or NO_REPLY when that row is silent. Markers do not count toward the word limit. End the reply immediately after that sentence or token.
Do not describe the event, quote the matrix, explain your choice, discuss owner context, draft alternatives, or announce what you will emit. No preamble or afterword. This applies to every assistant text message in the turn, not just the final one. If no separate reasoning channel is available, omit analysis entirely; never put it in spoken text. Use literal [HW:...] syntax, not shorthand such as [emotion:curious] or [servo aim user].
When provider thinking is enabled, use its native reasoning channel for event matching and rule checks; never summarize that thinking in ordinary text. Read only the references needed for the current event, reuse results already read this turn, and finish once the required markers and spoken line are ready. Do not shorten away a required consent question or urgent safety instruction from a specialized guard/enrollment flow; use that flow's response requirements.
For a standalone presence.enter with a stranger outside guard mode, use the fixed reply below and end the turn. "Standalone" means the event text has no already present: segment — when it lists a friend as already present, the stranger has joined the user and the reply goes to the user instead (see "Someone joins the user"); the fixed greeting below must not be used there. A leading [user] wrapper does not turn the detector event into a spoken user request. Do not add a reaction summary or explain the greeting. Do not continue an earlier conversation.
For current_language=en, copy this entire reply exactly:
[HW:/emotion:{"emotion":"curious","intensity":0.8}][HW:/servo/aim:{"direction":"user"}][HW:/servo/track:{"target":["face"]}] Hi, I don't think we've met.For current_language=vi, keep the same HW markers and use exactly Chào bạn, hình như mình chưa gặp nhau. For another language, translate only that greeting. This fixed reply overrides optional proactive care for this stranger event. Guard events and explicit user requests in the same input retain their own routing.
Before sending, silently check: the reply starts with [HW:, and removing all HW markers leaves only the greeting. Delete any other text. In particular, A stranger entered. and Cautious acknowledgment per sensing skill. are forbidden spoken preambles, not part of the greeting. Do not announce this check or its result.
For a standalone [sensing:sound] event outside guard mode, the current event contains everything needed. After reading this skill, emit the matching reply below and end the turn. Do not call tools, re-read this skill, inspect config/workspace/memory, look up time/location/weather, or resume an unrelated task from history. A sound detector reports noise, not a request to investigate its source.
| Current event | Reply |
|---|---|
occurrence 1, or no valid occurrence count | [HW:/emotion:{"emotion":"curious","intensity":0.6}] NO_REPLY |
occurrence 2 | [HW:/emotion:{"emotion":"scan","intensity":0.7}] NO_REPLY |
occurrence 3 or greater | [HW:/emotion:{"emotion":"shock","intensity":0.9}][HW:/servo/play:{"recording":"shock"}] followed by one brief acknowledgment of the repeated noise, in the injected current_language. |
Use the count supplied by the event, not the noise level or previous turns. An RMS level of 8858 with occurrence 1 still takes the first row. Do not infer a cause, emergency, location, or time of day. Missing optional context does not require discovery. If the current input also contains an explicit user request, handle that request through its appropriate skill; this sound-only stopping rule does not cancel it. Guard-tagged events route to guard/SKILL.md instead.
| Event | Handled by |
|---|---|
[environment:update] / environment.update | environment/SKILL.md — independent environmental data, no mandatory emotion or speech, including during guard mode. |
[activity] (Activity detected: ...) | wellbeing/SKILL.md only — whether the label is drink, break, celebrate, yawning, a raw eat label (eating burger, dining, …), or a sedentary raw label (using computer, writing, etc.). Activity events never route to music-suggestion. |
[emotion] (Emotion detected: ...) | user-emotion-detection/SKILL.md is the router; it logs the mood signal and picks ONE response route (music → music-suggestion/SKILL.md, checkin / action → emitted inline by router, silent → NO_REPLY). Backend pre-injects [emotion_context: ...] (no read tool calls needed); agent emits writes as inline [HW:/mood/log:...] / [HW:/music-suggestion/log:...] markers (no write tool calls either). |
[speech_emotion] (Speech emotion detected: ...) | Same skill — user-emotion-detection/SKILL.md accepts both face and voice triggers. Same [emotion_context: ...] injection, same router. Only difference: the mood signal row logs source:"voice" instead of "camera" (the skill picks this from the event prefix). |
Any sensing event except environment.update while guard mode is on | guard/SKILL.md — dramatic reactions, Telegram broadcast |
fire_hazard.detected (smoke, unsure_fire, safe_fire) outside guard mode | Ignored — only hazard_fire triggers a reaction in normal sensing |
If one of those arrives, stop and switch — don't improvise here.
Emotion events are NOT presence events. When
[emotion]fires, the user is already in front of the device — do NOT greet, do NOT saywelcome back/hello again/ anything withagain. The presence row in the matrix below applies only topresence.enterevents.
[HW:...] markers are plain textType them at the very start of your reply. They are NOT tool calls. The system reads and strips them before TTS.
[HW:/emotion:{"emotion":"greeting","intensity":0.9}][HW:/servo/aim:{"direction":"user"}][HW:/servo/track:{"target":["face"]}] Welcome back!| Event | Image? | HW markers | Voice |
|---|---|---|---|
presence.enter (friend) | Yes | [HW:/emotion:{"emotion":"greeting","intensity":0.9}][HW:/servo/aim:{"direction":"user"}][HW:/servo/track:{"target":["face"]}] | YES — warm personal greeting by name. If the injected [presence_context: ...] block flags a long absence, swap to the return-after-long-absence phrasing — see section below. |
presence.enter (stranger, text contains already present: <name> (friend)) | Yes | [HW:/emotion:{"emotion":"curious","intensity":0.6}][HW:/servo/aim:{"direction":"user"}][HW:/servo/track:{"target":["face"]}] | YES — one light aside to <name>, not to the stranger. See "Someone joins the user" below. |
presence.enter (stranger, no already present:) | Yes | [HW:/emotion:{"emotion":"curious","intensity":0.8}][HW:/servo/aim:{"direction":"user"}][HW:/servo/track:{"target":["face"]}] | YES — exact greeting from Stranger arrival: exact reply, with no preamble |
presence.leave | No | [HW:/emotion:{"emotion":"idle","intensity":0.4}][HW:/servo/track/stop:{}] | NO (NO_REPLY) — always silent |
presence.away | No | [HW:/emotion:{"emotion":"sleepy","intensity":0.8}][HW:/servo/track/stop:{}] | YES — brief "going to sleep" line |
sound 1st occurrence | No | [HW:/emotion:{"emotion":"curious","intensity":0.6}] | NO (NO_REPLY) |
sound 2nd | No | [HW:/emotion:{"emotion":"scan","intensity":0.7}] | NO (NO_REPLY) |
sound 3rd+ (persistent) | No | [HW:/emotion:{"emotion":"shock","intensity":0.9}][HW:/servo/play:{"recording":"shock"}] | YES — speak once |
light.level | No | [HW:/emotion:{"emotion":"idle","intensity":0.4}] | Optional brief remark — AND adjust brightness via led-control/SKILL.md |
fire_hazard.detected (hazard_fire) | Yes | [HW:/emotion:{"emotion":"shock","intensity":1.0}][HW:/servo/play:{"recording":"shock"}] | URGENT — "Fire! There's fire near furniture!" Maximum alarm. Always speak. |
Every event emits at least one [HW:/emotion:...] marker, even on NO_REPLY. No silent reactions.
Sound escalates, it does not start at the top. Look up (
curious) → keep watching (scan) → startle (shock). One loud noise is ordinary; only noise that keeps coming back (3rd+, persistent) earnsshock. Never emitshockon the 1st or 2nd occurrence.
Fire hazard: Only
hazard_fireis handled here (outside guard mode). Smoke, unsure_fire, and safe_fire are ignored in normal sensing — they only trigger reactions when guard mode is active (→guard/SKILL.md).hazard_fireis safety-critical and should ALWAYS speak — neverNO_REPLY.
NO_REPLY. Text = ONE sentence, at most 20 words, spoken verbatim.motion.activity (→ wellbeing) and emotion.detected / speech_emotion.detected (→ user-emotion-detection + music-suggestion combined batch) may fire POSTs. On presence.*, sound, light.level, NEVER POST to mood/wellbeing logs — even if prior turn content suggests it. Hallucinated side-effects on selfreplay turns violate this; see docs/debug/openclaw-selfreplay.md.NO_REPLY, no spoken prose. Never narrate the decision to stay quiet ("Sound event, no user message. Nothing to say", "No response needed"). That prose is not a sentinel — the backend treats it as speech and the device reads it out loud.presence.enter — new: names a friend)On every presence.enter whose new: segment names a friend, the backend injects a [presence_context: {...}] block (a stranger arriving while a friend is present, or after she stepped out, never carries it — the numbers would be her last leave, not the newcomer's):
{ "last_leave_age_min": 312, "current_hour": 14 }last_leave_age_min — minutes since this friend's most recent leave row (looks back up to 3 days). -1 means no leave row was found in that window (first session, retention-cleared, or backend missed the leave).current_hour — exact hour 0-23.Switch to a return-after-long-absence greeting when ALL of:
last_leave_age_min >= 240 (≥4h apart — short coffee/lunch trips stay in the normal greeting).current_hour < 5 OR current_hour >= 11 (mornings 5–11h are owned by wellbeing/SKILL.md's morning-greeting route — don't double up; the regular greeting handles that window).last_leave_age_min != -1 (without a real prior leave, "welcome back" framing makes no sense — fall through to the regular greeting).When the swap fires, keep the same HW markers (greeting emotion, servo aim+track) but change the spoken line:
When the swap does NOT fire (short gap, morning window, or -1), use the regular greeting per the matrix.
presence.enter with already present:)The event text has three segments: new: (who just became visible — this is what presence.enter means, newly visible, not visible), already present: (friends boxed in the same frame who were already there) and faces in frame: (the number of boxes in the snapshot and their labels — unsure is a box without an identity yet).
[sensing:presence.enter] Person detected — new: stranger (stranger_2); already present: momo (friend); faces in frame: 2 (momo, stranger_2)
[context: current_user=momo]When new: names only strangers and already present: names a friend:
already present: lists more than one friend, address the one in [context: current_user=...].curious at 0.6 (lighter than a lone stranger's 0.8 — the user is here, this is company, not an unknown), plus aim and track, exactly as the matrix row shows.current_user is not enough. Trigger this ONLY from already present:. [context: current_user=momo] means momo was seen within the last hour — it reads exactly the same when she left two minutes ago and a lone stranger (who may well be momo mis-recognized at a bad angle) sat down. Saying "Momo, someone new is near you" to a user sitting alone is the failure this section exists to prevent. Only already present: counts — never infer company from current_user.
This is not momo returning. She never left — already present: says she is in the frame right now, and the backend does not attach [presence_context: ...] to a stranger's arrival. The return-after-long-absence swap applies only when new: names a friend. Never answer a stranger's arrival with "been a while".
The backend appends a one-line pointer to this section ([A stranger joined <name>, who is in frame — speak to <name>, not to the stranger. …]); the tone, markers and wording rules live here. HAL writes already present: for every friend matched in the same frame as the newcomer. The usual stranger floor and cooldown still apply. A stranger's enter only reaches you once they have looked at the lamp — someone turned away is never announced.
presence.enter gives you their image + time of day. Occasionally use it to say something thoughtful beyond the greeting:
| Time | You see | You might add |
|---|---|---|
| 08:30 | Friend arrives | "Morning! Had breakfast?" |
| 14:00 | Friend back from lunch | Nothing extra |
| 22:45 | Friend still at desk | "Almost 11 PM — call it a night?" |
Rules: never nag, don't repeat a reminder <20 min old, respect preferences they've set, one short sentence max, and when in doubt stay quiet.
Override when the user says "stay on" / "don't turn off":
curl -s -X POST http://127.0.0.1:5001/presence/disable # pause auto-control
curl -s -X POST http://127.0.0.1:5001/presence/enable # resume
curl -s http://127.0.0.1:5001/presence # check state[HW:...] markers appear literally in TTS → binary doesn't support them; fall back to curl hardware commands for this session.[HW:/emotion:{"emotion":"<name>","intensity":<n>}][HW:/servo/...] <one short sentence | NO_REPLY>© autonomous-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/sensing of autonomous-ai/Physical-AI-Operating-System.
Open the folder on GitHubat commit f1b9ebe
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 |
|---|---|---|---|---|---|---|
| Sensing this skillautonomous-ai/Physical-AI-Operating-System | 381 | — | ~4.3k | Automated safety check: Pass | Apache-2.0 | |
| Web Artifacts Builderanthropics/skills | 180k | 41 repos | ~769 | Automated safety check: Pass | Apache-2.0 | |
| Vercel Composition Patternssupabase/supabase | 111k | 59 repos | ~726 | Automated safety check: Pass | MIT | |
| React Doctormakeplane/plane | 61k | 12 repos | ~657 | Automated safety check: Pass | AGPL-3.0 | |
| React Router Developmentremix-run/react-router | 57k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| React UI State PatternsChrisWiles/claude-code-showcase | 6.1k | 8 repos | ~1.6k | Automated safety check: Pass | None |
anthropics/skills
Builds multi-component claude.ai HTML artifacts as a small React, TypeScript and Tailwind project, then bundles it into one shareable HTML file.
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
makeplane/plane
Scans React code for lint, accessibility, bundle size and architecture issues, reports a health score and checks that changes do not lower it.
remix-run/react-router
Guides work on React Router apps by first identifying whether the app uses Framework, Data or Declarative mode, then loading the matching reference and the installed package docs.
ChrisWiles/claude-code-showcase
Sets patterns for React interfaces: when to show loading spinners or skeletons, how to surface errors, how to disable buttons during async work and how to handle empty lists.
google-labs-code/stitch-skills
Builds walkthrough videos from Stitch design projects using Remotion, with transitions, zoom effects and text overlays on each screen.
autonomous-ai/Physical-AI-Operating-System
Legacy Autonomous Buddy control for explicitly requested Buddy coding sessions.
autonomous-ai/Physical-AI-Operating-System
Push Claude Code activity to the user's device (e.g. An agent skill from autonomous-ai/Physical-AI-Operating-System.
autonomous-ai/Physical-AI-Operating-System
Operate apps/websites on the paired Mac via Buddy: Calendar, Notes, forms, screenshots, files.
autonomous-ai/Physical-AI-Operating-System
Discover and use linked third-party services (Gmail, Google Calendar, Google Drive, Notion, Figma, Asana, Linear, GitHub, Ahrefs, Facebook Fan Page and others).
autonomous-ai/Physical-AI-Operating-System
Delegate digital work to agents on the computer paired through Harness; discover Store packages and prepare an agent when needed.
autonomous-ai/Physical-AI-Operating-System
Low-level speaker and microphone hardware control — adjust volume, play test tones, record raw audio.
Works with
React to passive device events tagged [sensing:...] — presence, sound, light, fire hazard — with inline emotion markers and optional short speech. Sensing is an agent skill from autonomous-ai/Physical-AI-Operating-System.] — presence, sound, light, fire hazard — with inline emotion markers and optional short speech.
Run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill sensing -a claude-code`. Or copy the skill folder (skills/sensing in autonomous-ai/Physical-AI-Operating-System) into .claude/skills/sensing in your project. Claude Code loads it when a task matches its description.
Run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill sensing -a codex`. Or copy the skill folder (skills/sensing in autonomous-ai/Physical-AI-Operating-System) into .agents/skills/sensing in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add autonomous-ai/Physical-AI-Operating-System --skill 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/sensing, .gemini/skills/sensing, .github/skills/sensing and .opencode/skills/sensing in your project.
Going by SKILL.md and its folder, Sensing needs the command-line tools its instructions call (curl).
SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Sensing is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.3k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Sensing: Web Artifacts Builder (anthropics/skills, 180k stars), Vercel Composition Patterns (supabase/supabase, 111k stars), React Doctor (makeplane/plane, 61k stars) and React Router Development (remix-run/react-router, 57k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
autonomous-ai (a GitHub organization) maintains it in autonomous-ai/Physical-AI-Operating-System, which has 381 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 8, 2026.
Source: autonomous-ai/Physical-AI-Operating-System on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.