user-emotion-detection

user-emotion-detection is a skill for Claude Code, Codex from autonomous-ai/autonomous-os. It costs 77 tokens per session (2,877 once invoked), scanned A, original, Apache-2.0.

A routing tool that interprets detected user emotion from facial expressions or speech, records it through the mood tool, and chooses one response path.

In plain words
What is it for?
Use it when the camera or microphone reports an emotion, so the system can log it and choose music, a check-in, or another action.
Why use it?
It gives different emotion-related events one consistent process and prevents unrelated sensor events from being treated as emotions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when the camera or microphone reports an emotion, so the system can log it and choose music, a check-in, or another action.

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Install with agentmods
npx agentmods add skills/autonomous-ai/autonomous-os/user-emotion-detection
Install

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.

Any agent
npx skills add autonomous-ai/autonomous-os --skill user-emotion-detection
Clone the repo
git clone --depth 1 https://github.com/autonomous-ai/autonomous-os

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for user-emotion-detection

README.md
[![agentmods](https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/user-emotion-detection/github.svg)](https://agentmods.dev/skills/autonomous-ai/autonomous-os/user-emotion-detection)
Your own site
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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.

agentmods 80×15 button for user-emotion-detection

Your own site · 80×15
<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>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,877 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 9d ago against content hash 3a135d811c79, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

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
skills/user-emotion-detection/SKILL.md · 154 lines

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:

  1. The mood signal source field — "camera" for [emotion], "voice" for [speech_emotion].
  2. The label vocabulary — face uses Fear/Surprise/Disgust, voice uses Fearful/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" in thinking is not enough — if no [HW:/mood/log:...] marker appears in the reply text this turn, the skill failed. Every emotion.detected / speech_emotion.detected event = at least one mood signal log. No exceptions, no skips, no "already logged recently" reasoning. (curl POST 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.

Read the full file on GitHub · 154 lines

Files

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.

Changes

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.

  1. 9d ago First seen · 154 lines · 77 tokens per session scan A 3a135d811c79

Subscribe to this mod's changes

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.