research-review
Get a deep critical review of research from GPT using a secondary Codex agent. Use when user says \"review my research\", \"help me review\", \"get external review\", or wants critical feedback on research ideas, papers, or experimental results.
npx skills add majiayu000/claude-skill-registry --skill research-review-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.
# Research Review via a secondary Codex agent (xhigh reasoning) Get a multi-round critical review of research work from an external LLM with maximum reasoning depth. ## Constants - 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 xhigh reviewer. Use `--reviewer: oracle-pro` only when explicitly requested; if Oracle is unavailable, warn and fall back to Codex xhigh. ## Context: $ARGUMENTS ## Prerequisites - Use `spawn_agent` and `send_input` when the user has explicitly allowed delegation or subagents. - If delegation is not allowed, run the same review loop locally and preserve the same deliverable structure. ## Workflow ### Step 1: Gather Research Context Before calling the external reviewer, compile a comprehensive briefing: 1. Read project narrative documents (e.g., STORY.md, README.md, paper drafts) 2. Read any memory/notes files for key findings and experiment history 3. Identify: core claims, methodology, key results, known weaknesses ### Step 2: Initial Review (Round 1) Send a detailed prompt with xhigh reasoning: ``` spawn_agent: reasoning_effort:
- Constants
- Context: $ARGUMENTS
- Prerequisites
- Workflow
- Step 1: Gather Research Context
- Step 2: Initial Review (Round 1)
- Step 3: Iterative Dialogue (Rounds 2-N)
- Step 4: Convergence
- Step 5: Document Everything
- Step 6: Review Tracing
- Key Rules
- Prompt Templates
- For initial review:
- For experiment design:
What does the research-review skill do?
Get a deep critical review of research from GPT using a secondary Codex agent. Use when user says \"review my research\", \"help me review\", \"get external review\", or wants critical feedback on research ideas, papers, or experimental results.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill research-review-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.