ai-scientist-evaluatorlisted

# AI Scientist Evaluator Use this skill when Codex should behave like a skeptical reviewer panel rather than a research generator. Evaluate completed outputs, not just plans. ## Instructions 1. Confirm the request is evaluative. Use this skill to audit or compare existing outputs, not to perform the original research task. 2. Restate the exact task in one or two sentences so the review stays anchored to the real objective and required deliverables. 3. Inventory the submitted artifacts and note what is missing. Prefer primary artifacts over summaries: - notebooks, code, scripts, and workflow files - environment files, package versions, and runtime logs - figures, tables, and manuscript drafts - data provenance, accession lists, database versions, and citations - benchmark results, hardware notes, and task constraints 4. Choose the closest task profile from [`references/task_profiles.md`](references/task_profiles.md) and load the matching weights from [`assets/default_weight_profiles.yaml`](assets/default_weight_profiles.yaml). Use the primary scientific profile first for composite tasks, then add manuscript comments as a secondary layer. 5. Review with a four-person panel and synthesize a consensus: - scientific validity reviewer - computational and reproducibility reviewer - domain biology reviewer - writing and editorial reviewer 6. Apply hard gates before generous scoring. A submission is not publication-ready if requ