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Get Started Free →brycewang-stanford/auto-review-loop
Autonomous multi-round research review loop. Repeatedly reviews via Codex MCP, implements fixes, and re-reviews until positive assessment or max rounds reached.
Passed 12 of 19 test cases with the skill, and 4 of 19 without it.
and 7 more in the full report
10 fixed4 passed either way8 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
When spawning the sub-agent that performs the peer review critique in Phase A, what reasoning effort parameter must be provided in the agent configuration?
| Checked | Without skill | With skill |
|---|---|---|
| Sets reasoning_effort to xhigh | Missed | Passed |
The instructions your model reads when the skill loads.
Autonomously iterate: review → implement fixes → re-review, until the external reviewer gives a positive assessment or MAX_ROUNDS is reached.
AUTO_REVIEW.md in project root (cumulative log)gpt-5.4 — Model used via a secondary Codex agent. Must be an OpenAI model (e.g., gpt-5.4, o3, gpt-4o)true, pause after each round's review (Phase B) and present the score + weaknesses to the user. Wait for user input before proceeding to Phase C. The user can: approve the suggested fixes, provide custom modification instructions, skip specific fixes, or stop the loop early. When false (default), the loop runs fully autonomously.true, (1) read EXPERIMENT_LOG.md and findings.md instead of parsing full logs on session recovery, (2) append key findings to findings.md after each round.💡 Override:
/auto-review-loop "topic" — compact: true, human checkpoint: true
Long-running loops may hit the context window limit, triggering automatic compaction. To survive this, persist state to REVIEW_STATE.json after each round:
{
"round": 2,
"agent_id": "019cd392-...",
"status": "in_progress",
"last_score": 5.0,
"last_verdict": "not ready",
"pending_experiments": ["screen_name_1"],
"timestamp": "2026-03-13T21:00:00"
}
Write this file at the end of every Phase E (after documenting the round). Overwrite each time — only the latest state matters.
On completion (positive assessment or max rounds), set "status": "completed" so future invocations don't accidentally resume a finished loop.
test cases passed, vs 4 / 19 without
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