research-refine
Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-5.4 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.
npx skills add majiayu000/claude-skill-registry --skill research-refine --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 Refine: Problem-Anchored, Elegant, Frontier-Aware Plan Refinement Refine and concretize: **$ARGUMENTS** ## Overview Use this skill when the research problem is already visible but the technical route is still fuzzy. The goal is not to produce a bloated proposal or a benchmark shopping list. The goal is to turn a vague direction into a **problem -> focused method -> minimal validation** document that is concrete enough to implement, elegant enough to feel paper-worthy, and current enough to resonate in the foundation-model era. Four principles dominate this skill: 1. **Do not lose the original problem.** Freeze an immutable **Problem Anchor** and reuse it in every round. 2. **The smallest adequate mechanism wins.** Prefer the minimal intervention that directly fixes the bottleneck. 3. **One paper, one dominant contribution.** Prefer one sharp thesis plus at most one supporting contribution. 4. **Modern leverage is a prior, not a decoration.** When LLM / VLM / Diffusion / RL / distillation / inference-time scaling naturally fit the bottleneck, use them concretely. Do not bolt them on as buzzwords. ``` User input (PROBLEM + vague APPROACH) -> Phase 0 (Claude): Freeze Proble
- Overview
- Constants
- State Persistence (Checkpoint Recovery)
- Output Structure
- Workflow
- Initialization (Checkpoint Recovery)
- Phase 0: Freeze the Problem Anchor
- Phase 1: Build the Initial Proposal
- Phase 2: External Method Review (Round 1)
- Phase 3: Parse Feedback and Revise the Method
- Phase 4: Re-evaluation (Round 2+)
- Phase 5: Final Report and Logs
- Output Protocols
- Key Rules
What does the research-refine skill do?
Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-5.4 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.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill research-refine --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.