research-review

# 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-5.4` — Model used via a secondary Codex agent. Must be an OpenAI model (e.g., `gpt-5.4`, `o3`, `gpt-4o`) ## 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: xhigh message: | [Full research context + specific questions] Please act as a senior ML reviewer (NeurIPS/ICML level). Identify: 1. Logical gaps or unjustified claims 2. Missing experiments that would strengthen the story 3. Narrative weaknesses 4. Whether the contribution is sufficient for a top venue Please be brutally honest. ``` ### Step 3: Iterative Dialogue (Rounds 2-N) Use `send_input` with the returned agent id to continue the conver...