Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add autonomous-ai/autonomous-os --skill user-emotion-detectiongit clone --depth 1 https://github.com/autonomous-ai/autonomous-osWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/autonomous-ai/autonomous-os/user-emotion-detection)<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/user-emotion-detection"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/user-emotion-detection/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/user-emotion-detection"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/user-emotion-detection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00077 | $0.02877 |
| Opus 5 | $0.00039 | $0.01438 |
| Sonnet 5 | $0.00015 | $0.00575 |
| Haiku 4.5 | $0.00008 | $0.00288 |
Grade A, and why
user-emotion-detection scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> **EXECUTE, don't plan.** Before any reply (including `NO_REPLY`) you MUST embed a `[HW:/mood/log:{...}]` marker in the reply for this event (it fires the POST async via the runtime — see "What this skill produces" belo How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Emotion Detection
Strict Trigger
Runs only when this turn's input has one of:
[emotion] Emotion detected: <EmotionName>— facial expression from camera.[speech_emotion] Speech emotion detected: <EmotionName>— vocal expression from microphone.
Both are first-class triggers and route through the same logic below. The only differences are:
- The mood signal
sourcefield —"camera"for[emotion],"voice"for[speech_emotion]. - The label vocabulary — face uses
Fear/Surprise/Disgust, voice usesFearful/Surprised/Disgusted. The mapping table below covers both; they bucket identically.
For any other event ([sensing:presence.*], [activity], [sensing:sound], [sensing:light.*], …) → STOP. No tool calls. Don't infer emotion from older turns — every signal must come from a real [emotion] or [speech_emotion] event in THIS turn.
EXECUTE, don't plan. Before any reply (including
NO_REPLY) you MUST embed a[HW:/mood/log:{...}]marker in the reply for this event (it fires the POST async via the runtime — see "What this skill produces" below). Writing "I will post a mood signal" inthinkingis not enough — if no[HW:/mood/log:...]marker appears in the reply text this turn, the skill failed. Everyemotion.detected/speech_emotion.detectedevent = at least one mood signal log. No exceptions, no skips, no "already logged recently" reasoning. (curlPOST is the documented fallback only when the HW marker would break the body regex; do not use it as the default.)
This skill is silent. It only logs mood data — no spoken reply needed. All steps stay in
thinking. If you want to speak, follow normal sensing reply rules. NEVER narrate mood logging, mapping, or workflow steps in the reply.
EMOTION TURN OUTPUT CONTRACT — highest priority. For a triggered
[emotion]/[speech_emotion]turn, your entire final assistant message must be exactly one of these two shapes:[zero or more HW markers] NO_REPLY [zero or more HW markers] <one natural sentence addressed to the user>Nothing may appear before, between, or after those parts. In particular, do not output the detected label or confidence; describe the cue as weak; name a bucket, route, rule, source, prefix, marker, log, decision, or mood; state what you are about to do; draft a line; or count its words/sentences. Those are private scratch work, never user-facing text. Do the writes via HW markers, then start immediately with the first word the user should hear. Bad:
Emotion: Anger. Weak camera cue. Route = checkin. Let me compose...Good:[HW:...] That sounds rough — I'm right here.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 154 lines · 77 tokens per session scan A 3a135d811c79
user-emotion-detection is a skill published in the GitHub repository autonomous-ai/autonomous-os (286 stars, last pushed yesterday), licensed Apache-2.0. It adds 77 tokens to every session and 2,877 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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