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Agent skill

Autoresearch

by Yeachan-Heo in Yeachan-Heo/oh-my-claudecode

Stateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior

MITAuto-check passedAgent Workflows

Install Autoresearch

skills CLI
$ npx skills add Yeachan-Heo/oh-my-claudecode --skill autoresearch -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Yeachan-Heo/oh-my-claudecode autoresearch --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Yeachan-Heo/oh-my-claudecode.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/autoresearch .claude/skills/autoresearch && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
autoresearch
GitHub stars
40k
Token cost
~894 tokens
SKILL.md length
379 words
Files
1
Skills in repo
47
Repo updated
First seen
Licence
MIT

At a glance

Stateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior

  • Works in 4 steps: Confirm a single mission exists and… → Ensure mode/state is active for… → On every iteration → …
  • Tasks that involve Autonomous loops
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve Architecture decision records

What it does

Autoresearch is an agent skill from Yeachan-Heo/oh-my-claudecode. Stateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior

Its SKILL.md is about 890 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Autonomous loops and Architecture decision records. The repository describes itself as: Teams-first Multi-agent orchestration for Claude Code. The licence is MIT.

When your agent uses it

  • Tasks that involve Autonomous loops
  • Tasks that involve Architecture decision records

Example prompts

  • “/autoresearch”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Confirm a single mission exists and evaluator setup is already available.
  2. Ensure mode/state is active for autoresearch and records
  3. On every iteration
  4. Stop when

What it can do on your machine

Read from SKILL.md and the folder at commit 454bae0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Autoresearch loads about 894 tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 379 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~894

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Yeachan-Heo/oh-my-claudecode at commit 454bae0, republished under its MIT licence (© Yeachan-Heo). 379 words, ~894 tokens.

Download SKILL.mdSave it as .claude/skills/autoresearch/SKILL.md (or your agent's skills folder).
name
autoresearch
description
Stateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior
argument-hint
[--mission-dir <path>] [--max-runtime <duration>] [--cron <spec>] [--resume <run-id>]
level
4
<Purpose>
Autoresearch is a stateful skill for bounded, evaluator-driven iterative improvement. It owns one mission at a time, keeps iterating through non-passing results, records each evaluation and decision as durable artifacts, and stops only when an explicit max-runtime ceiling or another explicit terminal condition is reached.
</Purpose>

<Use_When>

  • You already have a mission and evaluator from /deep-interview --autoresearch
  • You want persistent single-mission improvement with strict evaluation
  • You need durable experiment logs under .omc/autoresearch/
  • You want a supported path for periodic reruns via Claude Code native cron </Use_When>

<Do_Not_Use_When>

  • You need evaluator generation at runtime — use /deep-interview --autoresearch first
  • You need multiple missions orchestrated together — v1 forbids that
  • You want the deprecated omc autoresearch CLI flow — it is no longer authoritative </Do_Not_Use_When>
<Contract>
- Single-mission only in v1
- Mission setup/evaluator generation stays in `deep-interview --autoresearch`
- Evaluator output must be structured JSON with required boolean `pass` and optional numeric `score`
- Non-passing iterations do **not** stop the run
- Stop conditions are explicit and bounded, with max-runtime as the primary strict stop hook
</Contract>

<Required_Artifacts> Canonical persistent storage lives under .omc/autoresearch/<mission-slug>/ and/or .omc/logs/autoresearch/<run-id>/.

Minimum required artifacts:

  • mission spec
  • evaluator script or command reference
  • per-iteration evaluation JSON
  • markdown decision logs

Recommended canonical shape:

text
.omc/autoresearch/<mission-slug>/
  mission.md
  evaluator.json
  runs/<run-id>/
    evaluations/
      iteration-0001.json
      iteration-0002.json
    decision-log.md

Reuse existing runtime artifacts when available rather than duplicating them unnecessarily. </Required_Artifacts>

<Workflow>
1. Confirm a single mission exists and evaluator setup is already available.
2. Ensure mode/state is active for `autoresearch` and records:
   - mission slug/dir
   - evaluator reference
   - iteration count
   - started/updated timestamps
   - explicit max-runtime or deadline
3. On every iteration:
   - run exactly one experiment/change cycle
   - run the evaluator
   - persist machine-readable evaluation JSON
   - append a human-readable markdown decision log entry
   - continue even when evaluation does not pass
4. Stop when:
   - max-runtime ceiling is reached
   - user explicitly cancels
   - another explicit terminal condition is recorded by the runtime
</Workflow>
Show full SKILL.md (86 more words)Show less

<Cron_Integration> Claude Code native cron is a supported integration point for periodic mission enhancement. In v1, prefer documenting/configuring cron inputs over building a large scheduler UI.

If cron is used:

  • keep one mission per scheduled job
  • preserve the same mission/evaluator contract
  • append new run artifacts rather than overwriting prior experiments </Cron_Integration>

<Execution_Policy>

  • Do not hand execution back to omc autoresearch
  • Do not create multi-mission orchestration
  • Prefer reusing src/autoresearch/* runtime/schema helpers where they already match the stricter contract
  • Keep logs useful to humans, not only machines </Execution_Policy>

© Yeachan-Heo, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/autoresearch of Yeachan-Heo/oh-my-claudecode.

Open the folder on GitHubat commit 454bae0

Compare with similar skills

Autoresearch next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Autoresearch compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Autoresearch this skillYeachan-Heo/oh-my-claudecode40k—~894Automated safety check: PassMIT
Autoresearchjmstar85/oh-my-githubcopilot159—~261Automated safety check: PassMIT
Autoresearch Iteration Loopuditgoenka/autoresearch6.5k1 repos~2kAutomated safety check: PassMIT
Install Loop Engineeringcobusgreyling/loop-engineering11k1 repos~648Automated safety check: PassMIT
LoopX Self Repairloopx-project/loopx6.2k—~2.2kAutomated safety check: PassApache-2.0
PUA Looptanweai/pua20k—~1.1kAutomated safety check: PassMIT

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Categories

Questions about Autoresearch

What does Autoresearch do?

Stateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior. Autoresearch is an agent skill from Yeachan-Heo/oh-my-claudecode.

When should I use Autoresearch?

Autoresearch fits situations like: tasks that involve Autonomous loops; tasks that involve Architecture decision records.

How do I install Autoresearch in Claude Code?

Run `npx skills add Yeachan-Heo/oh-my-claudecode --skill autoresearch -a claude-code`. Or copy the skill folder (skills/autoresearch in Yeachan-Heo/oh-my-claudecode) into .claude/skills/autoresearch in your project. Claude Code loads it when a task matches its description.

How do I install Autoresearch in Codex?

Run `npx skills add Yeachan-Heo/oh-my-claudecode --skill autoresearch -a codex`. Or copy the skill folder (skills/autoresearch in Yeachan-Heo/oh-my-claudecode) into .agents/skills/autoresearch in your project. Codex loads it when a task matches its description.

Can I use Autoresearch in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Yeachan-Heo/oh-my-claudecode --skill autoresearch -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/autoresearch, .gemini/skills/autoresearch, .github/skills/autoresearch and .opencode/skills/autoresearch in your project.

What does Autoresearch need to run?

SKILL.md names no scripts, command-line tools or credentials: Autoresearch is instructions for the agent only.

Does Autoresearch access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Autoresearch safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Autoresearch use?

Autoresearch is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Autoresearch use?

About 894 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Autoresearch?

Skills that share tags, products or a category with Autoresearch: Autoresearch (jmstar85/oh-my-githubcopilot, 159 stars), Autoresearch Iteration Loop (uditgoenka/autoresearch, 6.5k stars), Install Loop Engineering (cobusgreyling/loop-engineering, 11k stars) and LoopX Self Repair (loopx-project/loopx, 6.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Autoresearch?

Yeachan-Heo (a GitHub user) maintains it in Yeachan-Heo/oh-my-claudecode, which has 39,751 GitHub stars. The repository holds 47 skills in this directory. The repository was last updated on October 8, 2026.

Source: Yeachan-Heo/oh-my-claudecode on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.