Individual skill

research-refine

Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-6-Astra review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.

skills/skills-codex/research-refine/SKILL.md

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Last checked: Nov 9, 2026

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Repository stars (not skill ratings): 19,037
Repository last updated: Nov 8, 2026
License: MIT

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ai-research Repository topic
autonomous-agent Repository topic
claude-code Repository topic
codex Repository topic
mcp Repository topic
ml-research Repository topic
paper-review Repository topic
research-automation Repository topic
ai-tools Repository topic
claude Repository topic
research Derived category

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# Research Refine: Problem-Anchored, Elegant, Frontier-Aware Plan Refinement

> **Before each reviewer slot**, follow [Selectable Reviewers](../shared-references/reviewer-backends.md):
> resolve invocation → `.aris/reviewer.json` → Codex default (fresh native reviewer)
> with `reviewer_route.py` through the canonical helper resolver, preserving this
> slot's tier, fresh contexts, source/image inputs and deterministic gates.
> Codex examples/pins below apply only to `backend=codex`; other routes use their
> own first-call/reply contract. Save the route and actual returned identity;
> unavailable selections are `REVIEW_UNAVAILABLE`. Classify acceptance from actual
> families/completion/scope. Forward invocation reviewer/model/effort overrides
> to reviewer-bearing children. Generation workers are unchanged.


Refine and concretize: **$ARGUMENTS**