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 music-suggestiongit 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/music-suggestion)<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/music-suggestion"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/music-suggestion/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/music-suggestion"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/music-suggestion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 98 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00125 | $0.02428 |
| Opus 5 | $0.00063 | $0.01214 |
| Sonnet 5 | $0.00025 | $0.00486 |
| Haiku 4.5 | $0.00013 | $0.00243 |
Grade A, and why
music-suggestion 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 yesterday.
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.
curl -s http://127.0.0.1:5001/audio/status & How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Music Suggestion (Proactive)
unknownusers count. Always run suggestion checks whencurrent_useris"unknown"— speak only, no DM. Never skip because the user is unknown/unconfirmed.
Triggers
Only one trigger: Mood — after logging a mood decision that is suggestion-worthy (sad, stressed, tired, excited, happy, bored). Activity events ([activity] Activity detected: ..., whether sedentary, drink/break, or celebrate) route to wellbeing/SKILL.md and never to this skill.
User attribution
{name} MUST come from [context: current_user=X] tag. If missing, use "unknown". NEVER infer from memory or chat history.
What to read (pre-fetched in [emotion_context: ...])
The backend injects everything you need on emotion.detected (face) or speech_emotion.detected (voice) — same block, same fields:
audio_playing(bool) — replacesGET /audio/status.last_suggestion_age_min(int,-1if none today) — replacesmusic-suggestion-history?last=1.prior_decision+is_decision_stale— replacesmood-history?kind=decision&last=1. The freshly synthesized decision from THIS turn still lives in yourthinking.audio_recent({track,duration_s,stopped}) — replacesaudio/history?last=1.music_pattern_for_hour({preferred_genre,strength,peak_hour}ornull) — replacescat patterns.jsonmatching by current hour ±1.suggestion_worthy(bool) — pre-applied bucket gate (true forsad/stressed/tired/excited/happy/bored).mapped_mood— convenient mirror ofuser-emotion-detection's mapping; useful when no fresh decision exists yet.
Do NOT fire any read tool calls when this block is present.
Fallback (only if [emotion_context: ...] is missing)
If the message has no context block (pre-fetch failed), fall back to the concurrent GET batch:
curl -s http://127.0.0.1:5001/audio/status &
curl -s "http://127.0.0.1:5000/api/openclaw/music-suggestion-history?user={name}&last=1" &
curl -s "http://127.0.0.1:5000/api/openclaw/mood-history?user={name}&kind=decision&last=1" &
curl -s "http://127.0.0.1:5001/audio/history?person={name}&last=1" &
cat /root/local/users/{name}/habit/patterns.json 2>/dev/null &
wait
What ships with it
1 file 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.
- yesterday Changed 96ecc6456780
- 12d ago First seen · 144 lines · 125 tokens per session scan A 63df17ba006c
music-suggestion is a skill published in the GitHub repository autonomous-ai/autonomous-os (325 stars, last pushed today), licensed Apache-2.0. It adds 125 tokens to every session and 2,428 once invoked, about $0.0006 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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