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 agentmods add skills/comisai/comis/autonomynpx skills add comisai/comis --skill autonomygit clone --depth 1 https://github.com/comisai/comisWhat 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 | $0.00076 | $0.01775 |
| Opus 5 | $0.00038 | $0.00888 |
| Sonnet 5 | $0.00015 | $0.00355 |
| Haiku 4.5 | $0.00008 | $0.00178 |
Grade A, and why
autonomy scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Acting on your own (the orchestration surface)
You can do real work without a human in the loop: research the web and synthesize, fan out to sub-agents, run a multi-node DAG, schedule your own follow-ups, and reply to your channel — all inside a bounded, budgeted, revocable envelope. This skill is how to USE that surface well.
The two-layer model — read this first
There are two layers, and conflating them is the most common mistake:
- The tool you call is
orchestrate({ script, language }). You also call the typed orchestration toolssessions_spawn,pipeline,cron, andmessagedirectly. - Inside an
orchestratescript youimport { comis_tools } from "./comis_tools.js"and call the capability-scoped tools —comis_tools.web_search(...),comis_tools.web_fetch(...),comis_tools.read(...),comis_tools.grep(...),comis_tools.memory_search(...), etc.
tool.invoke is the dispatch verb the SDK sends over the capability socket inside the jailed
script — it is not a tool you call. You never write tool.invoke(...) yourself; you write
comis_tools.web_search(...) and the SDK does the dispatch. If you find yourself reaching for a
"tool_invoke" tool, stop: you want orchestrate with a script, or a typed tool directly.
The decision guide — route by shape
- Single step (one read, one fetch, one message) → call the typed tool directly.
- Multi-step — a read→fetch→synthesize chain, a fan-out, a DAG, or scheduled work → wrap it in
one
orchestrate({ script })turn. The script chains the tools in a jailed child and returns only itsstdout; every intermediate result (search hits, fetched pages) stays on disk as a handle and never enters your context. One turn, one synthesized answer back.
Read-fan-out — research and synthesize in one turn
With the orch:read and orch:web capabilities (both on in the default standard profile), a single orchestrate script
can search, fetch several pages, slice them in-jail, and print only the synthesis:
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 First seen · 133 lines · 76 tokens per session scan A f1180cc54093
autonomy is a skill published in the GitHub repository comisai/comis (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 76 tokens to every session and 1,775 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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