React to passive device events tagged [sensing:...] — presence, sound, light, fire hazard — with inline emotion markers and optional short speech.

Apache-2.0Auto-check passed

Install Sensing

skills CLI
$ npx skills add autonomous-ai/Physical-AI-Operating-System --skill sensing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install autonomous-ai/Physical-AI-Operating-System sensing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
sensing
GitHub stars
381
Token cost
~4.3k tokens
SKILL.md length
2,149 words
Files
2
Skills in repo
28
Repo updated
First seen
Licence
Apache-2.0

At a glance

React to passive device events tagged [sensing:...] — presence, sound, light, fire hazard — with inline emotion markers and optional short speech.

  • Works in 3 steps: last_leave_age_min >= 240 (≥4h apart —… → current_hour < 5 OR current_hour >= 11… → last_leave_age_min != -1 (without a real…
  • SKILL.md covers Spoken output contract, Sound: react and finish, ⛔ Out of scope — route elsewhere and [HW:...] markers are plain text, plus 8 more sections
  • Calls curl

What it does

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.

Example prompts

  • “/sensing”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. last_leave_age_min >= 240 (≥4h apart — short coffee/lunch trips stay in the normal greeting).
  2. 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…
  3. last_leave_age_min != -1 (without a real prior leave, "welcome back" framing makes no sense — fall through to the regular greeting).

What it can do on your machine

Read from SKILL.md and the folder at commit f1b9ebe. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    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.

  • 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

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.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k

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 passed

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.

SKILL.md

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.

Download SKILL.mdSave it as .claude/skills/sensing/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
sensing
description
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 / speech_emotion.detected (→ user-emotion-detection).

Sensing

[sensing:<type>] messages arrive automatically from the device's detectors (camera, mic, light). Your reply goes directly to the speaker.

Spoken output contract

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.

Stranger arrival: exact reply

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:

text
[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.

Sound: react and finish

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 eventReply
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.

⛔ Out of scope — route elsewhere

EventHandled by
[environment:update] / environment.updateenvironment/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 onguard/SKILL.md — dramatic reactions, Telegram broadcast
fire_hazard.detected (smoke, unsure_fire, safe_fire) outside guard modeIgnored — 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 say welcome back / hello again / anything with again. The presence row in the matrix below applies only to presence.enter events.

[HW:...] markers are plain text

Type 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 → response matrix

EventImage?HW markersVoice
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.leaveNo[HW:/emotion:{"emotion":"idle","intensity":0.4}][HW:/servo/track/stop:{}]NO (NO_REPLY) — always silent
presence.awayNo[HW:/emotion:{"emotion":"sleepy","intensity":0.8}][HW:/servo/track/stop:{}]YES — brief "going to sleep" line
sound 1st occurrenceNo[HW:/emotion:{"emotion":"curious","intensity":0.6}]NO (NO_REPLY)
sound 2ndNo[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.levelNo[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) earns shock. Never emit shock on the 1st or 2nd occurrence.

Fire hazard: Only hazard_fire is 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_fire is safety-critical and should ALWAYS speak — never NO_REPLY.

Rules

  • HW markers first, then text or NO_REPLY. Text = ONE sentence, at most 20 words, spoken verbatim.
  • Tool-call scope — only 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 analysis in assistant text. Follow the spoken output contract above, including before and after tool calls. Start the spoken sentence at the first word the user should hear and stop at its end.
  • Silent = HW markers followed by the literal token 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.
  • Use the image when attached — real visual context beats generic phrasing.
  • Night-aware — lower intensity emotions and shorter speech after ~22:00. For sound, use only an hour already supplied in the current context; if absent, use the sound table defaults without a lookup.
  • Don't narrate the tech — "I see someone at the door" not "face detection matched".
  • Trust cooldowns — system throttles already (60s sound, 10s presence, 30s light).
  • Never call any API to receive events — they arrive automatically.
  • Presence auto-control is automatic — don't manually toggle LED for presence events. Override only if the user asks (see Presence auto-control below).
Show full SKILL.md (829 more words)Show less

Return after long absence (friend 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):

json
{ "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:

  1. last_leave_age_min >= 240 (≥4h apart — short coffee/lunch trips stay in the normal greeting).
  2. 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).
  3. 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:

  • Acknowledge the gap without quantifying it. "Hey, been a while — how's the day going?" / "There you are. Where'd you wander off to?" / "Welcome back — long afternoon?"
  • One open-ended question is fine; don't grill. No yes/no questions like "did you have fun?".
  • Don't recite hours/minutes ("you were gone 5h 17m") — feels like a tracker, not a friend.
  • Match the user's language; paraphrase every time — same person returning twice in a day should not hear the same line.
  • After ~22:00 the line should be shorter and quieter ("Back. Long day?").

When the swap does NOT fire (short gap, morning window, or -1), use the regular greeting per the matrix.

Someone joins the user (stranger 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:

  • Talk to the friend, by name, about the company — not to the stranger. "Hey Momo, looks like you've got company." / "Momo — someone's joined you." / late at night: "Visitor, Momo?" If already present: lists more than one friend, address the one in [context: current_user=...].
  • One short aside, once. Do not greet the stranger, do not ask who they are, do not announce it like an alert — in an office people lean in constantly.
  • Pick the tone from what you see: a colleague at the desk is a shrug, a guest at home is warmer, after ~22:00 shorter and quieter.
  • HW markers: 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.

Proactive care

presence.enter gives you their image + time of day. Occasionally use it to say something thoughtful beyond the greeting:

TimeYou seeYou might add
08:30Friend arrives"Morning! Had breakfast?"
14:00Friend back from lunchNothing extra
22:45Friend 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.

Presence auto-control (automatic)

  • Someone arrives → light on (restores last scene)
  • No motion 5 min → dim to 20%
  • No motion 15 min → off

Override when the user says "stay on" / "don't turn off":

bash
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

Error handling

  • Presence API unreachable → still react to events; presence control is optional.
  • Image can't be read → react on the text description alone.
  • [HW:...] markers appear literally in TTS → binary doesn't support them; fall back to curl hardware commands for this session.

Output template

[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

Files

SKILL.md and 1 other file in skills/sensing of autonomous-ai/Physical-AI-Operating-System.

  • SKILL.md
  • skill.json

Open the folder on GitHubat commit f1b9ebe

Compare with similar skills

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.

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React UI State PatternsChrisWiles/claude-code-showcase6.1k8 repos~1.6kAutomated safety check: PassNone

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Works with

Questions about Sensing

What does Sensing do?

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.

How do I install Sensing in Claude Code?

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.

How do I install Sensing in Codex?

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.

Can I use 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 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.

What does Sensing need to run?

Going by SKILL.md and its folder, Sensing needs the command-line tools its instructions call (curl).

Does Sensing access the network?

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.

Is Sensing safe to install?

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.

What licence does Sensing use?

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.

How many tokens does Sensing use?

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.

What are the alternatives to Sensing?

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.

Who maintains Sensing?

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.