
Research Review via External Reviewer
Gets a multi-round, adversarial critical review of your research from an external AI reviewer (Codex by default).
- Stars
- 18,482
- Licence
- MIT
- Files
- 1 file
What it does
When installed, the agent gathers your research notes, drafts and results into a briefing file, then sends it to a separate AI reviewer (by default OpenAI Codex, or Gemini, Grok, Claude Code or a manual route you choose). The reviewer is told to act like a strict ML conference reviewer and look for logical gaps, missing experiments, weak narrative and whether the contribution is strong enough for a top venue. The agent can continue the same review thread across rounds.
Great for
- Researchers who want a harsh second opinion on a paper draft or experimental results before submission
- Teams that want a cross-model review rather than relying on a single AI's judgement
Skip it if
- Quick proofreading or grammar checks, since it is aimed at deep methodological critique and is slow and token-expensive
- Confidential or unpublished work you do not want sent to a third-party AI service, because the briefing is transmitted to the chosen reviewer backend
Try asking
- “Review my research and tell me where the logic is weakest”
- “Get external review of my experimental results before I submit to NeurIPS”
- “Help me review this research idea and list missing experiments”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the MIT licence and an attribution note.
research-review.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip research-review.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip research-review.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Put your key narrative documents and notes in the project before running it, so the briefing is complete
- Keep the same review thread for follow-up rounds rather than starting over, to preserve reviewer memory
- Do not schedule it with /loop or cron; run it once work is ready, as the skill itself instructs
What's inside
- SKILL.md
Redistributed unmodified from wanshuiyin/Auto-claude-code-research-in-sleep under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.