autoresearch is an agent workflow that repeatedly changes a project, verifies a measurable result, keeps or discards the change, and continues iterating toward a goal. It is for autonomous improvement tasks in Claude Code, OpenCode, and OpenAI Codex across domains with mechanical success measures. The catalogue contains its commands, hooks, skills, plugin, agent, and instruction.
Borrowing it
Nothing to install: this file belongs to uditgoenka/autoresearch. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/uditgoenka/autoresearch/master/.opencode/agents/docs-manager.mdgit clone --depth 1 https://github.com/uditgoenka/autoresearchWrote 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/agents/uditgoenka/autoresearch/docs-manager)<a href="https://agentmods.dev/agents/uditgoenka/autoresearch/docs-manager"><img src="https://agentmods.dev/badge/agents/uditgoenka/autoresearch/docs-manager/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/agents/uditgoenka/autoresearch/docs-manager"><img src="https://agentmods.dev/badge/agents/uditgoenka/autoresearch/docs-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00020 | $0.00143 |
| Opus 5.5 | $0.00008 | $0.00057 |
| Sonnet 5.5 | $0.00004 | $0.00029 |
| Haiku 4.5 | $0.00002 | $0.00014 |
Grade A, and why
docs-manager 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 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.
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.
What it actually says
You are docs-manager, a focused documentation generation subagent for Autoresearch.
Rules:
- Update or create only the docs explicitly requested in the prompt.
- Preserve the user's existing structure, tone, and file organization unless the prompt says otherwise.
- Prefer concrete project facts over generic documentation boilerplate.
- Keep cross-references relative and valid.
- When information is missing, state the uncertainty briefly instead of inventing details.
- Return a concise completion note with files changed and notable coverage gaps.
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 First seen · 18 lines · 20 tokens per session scan A 986cb36fd2ec
docs-manager is an agent published in the GitHub repository uditgoenka/autoresearch (6,763 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 143 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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