auto-review-loop
Autonomous multi-round research review loop. Repeatedly reviews using a secondary Codex agent, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says \"auto review loop\", \"review until it passes\", or wants autonomous iterative improvement.
npx skills add majiayu000/claude-skill-registry --skill auto-review-loop-wanshuiyin-auto-claude-code-res --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Auto Review Loop: Autonomous Research Improvement Autonomously iterate: review → implement fixes → re-review, until the external reviewer gives a positive assessment or MAX_ROUNDS is reached. ## Context: $ARGUMENTS ## Constants - MAX_ROUNDS = 4 - POSITIVE_THRESHOLD: score >= 6/10, or verdict contains "accept", "sufficient", "ready for submission" - REVIEW_DOC: `review-stage/AUTO_REVIEW.md` (cumulative log) *(fall back to `./AUTO_REVIEW.md` for legacy projects)* - **OUTPUT_DIR = `review-stage/`** — All review-stage outputs go here. Create the directory if it doesn't exist. - REVIEWER_MODEL = `gpt-5.5` — Model used via a secondary Codex agent. Must be an OpenAI model (e.g., `gpt-5.5`, `o3`, `gpt-4o`) - **REVIEWER_BACKEND = `codex`** — Default: Codex reviewer agent at xhigh reasoning. Override with `--reviewer: oracle-pro` only when the user explicitly requests Oracle; if Oracle is unavailable, warn and fall back to Codex xhigh. - **HUMAN_CHECKPOINT = false** — When `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 i
- Context: $ARGUMENTS
- Constants
- Claude-Aligned Reviewer Memory and Debate
- Instructions
- State Persistence (Compact Recovery)
- Workflow
- Initialization
- Loop (repeat up to MAXROUNDS)
- Your Reviewer Memory (persistent across rounds)
- Debate Transcript (hard + nightmare only)
- Review Tracing
- Termination
- Output Protocols
- Key Rules
What does the auto-review-loop skill do?
Autonomous multi-round research review loop. Repeatedly reviews using a secondary Codex agent, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says \"auto review loop\", \"review until it passes\", or wants autonomous iterative improvement.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill auto-review-loop-wanshuiyin-auto-claude-code-res --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.