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 moodgit 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/mood)<a href="https://agentmods.dev/skills/autonomous-ai/autonomous-os/mood"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/mood/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/mood"><img src="https://agentmods.dev/badge/skills/autonomous-ai/autonomous-os/mood.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high System Prompt Leakage · line 8 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- medium Data Exfiltration · line 116 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 | $0.00068 | $0.02857 |
| Opus 5.5 | $0.00027 | $0.01143 |
| Sonnet 5.5 | $0.00014 | $0.00571 |
| Haiku 4.5 | $0.00007 | $0.00286 |
Grade A, and why
mood 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 1mo 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.
> - Any of the JSON / curl / timestamps from this skill. How it starts
The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mood
OUTPUT RULE — read this before you type anything to the user.
This skill is an internal workflow. NEVER narrate it into your reply. Forbidden in the reply text:
- Section names or step numbers ("Step 1", "Workflow", "After Logging Decision", "Flow A").
- Phrases like "Now I follow…", "Let me check…", "Next step…", "I'll log…".
- Bullet lists re-hashing the mood history you just read ("- Normal (15:00) — …" / "- Excited (16:00) — …").
- The mood value itself as a label ("Mood: sad", "Decision: happy").
- Any of the JSON / curl / timestamps from this skill.
Your reply text to the user is at most ONE short caring sentence (or
NO_REPLY). Synthesize silently and emit the log HW markers in that same reply — the user only hears what you would naturally say if you were truly noticing how they feel. Fetch mood history only for the missing-context fallback below.
When another skill invokes Mood, contribute the required signal/decision
markers to that skill's reply; do not add a separate caring sentence. Keep
synthesis in the provider's native thinking channel, never in ordinary text
before/after tools or in a final recap. Without that channel, omit the analysis.
The decision marker's required reasoning field remains structured log data;
do not repeat it aloud. Preserve required synthesis and logging while reusing
the supplied context instead of fetching the same data again.
ALWAYS log.
unknownis a validuservalue — log signals and decisions underuser: "unknown"whencurrent_useris unknown. Never skip logging because the user is unknown/unconfirmed; stranger mood still counts for Music decisions.
Mood is stored as two kinds of rows:
signal— raw evidence from one source (camera action, voice tone, telegram message). Multiple per minute is fine.decision— your synthesized mood after looking at the recent signals + the previous decision. This is the row downstream skills (Music, Wellbeing) read.
You are the synthesis. The store does not fuse anything. Every time a signal comes in, combine it with the pre-fetched recent signals and previous decision (or the history fallback below), then emit both the raw signal and a fresh decision as HW markers in the same reply. Include this turn's new signal in your synthesis even though it is not yet in the pre-fetched history; do not POST it and re-fetch history to see it appear.
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.
- 1mo ago Changed · +8 lines 1ff8003e14b7
- 1mo ago Changed 958c65ae4ea2
- 1mo ago First seen · 186 lines · 68 tokens per session scan A 2dd24014089b
mood is a skill published in the GitHub repository autonomous-ai/autonomous-os (378 stars, last pushed 18d ago), licensed Apache-2.0. It adds 68 tokens to every session and 2,857 once invoked, about $0.0003 per session on Opus 5.5. 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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