experiment-plan
Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.
npx skills add majiayu000/claude-skill-registry --skill experiment-plan-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.
# Experiment Plan: Claim-Driven, Paper-Oriented Validation Refine and concretize: **$ARGUMENTS** ## Overview Use this skill after the method is stable enough that the next question becomes: **what exact experiments should we run, in what order, to defend the paper?** If the user wants the full chain in one request, prefer `/research-refine-pipeline`. The goal is not to generate a giant benchmark wishlist. The goal is to turn a proposal into a **claim -> evidence -> run order** roadmap that supports four things: 1. the method actually solves the anchored problem 2. the dominant contribution is real and focused 3. the method is elegant enough that extra complexity is unnecessary 4. any frontier-model-era component is genuinely useful, not decorative ## Constants - **OUTPUT_DIR = `refine-logs/`** — Default destination for experiment planning artifacts. - **MAX_PRIMARY_CLAIMS = 2** — Prefer one dominant claim plus one supporting claim. - **MAX_CORE_BLOCKS = 5** — Keep the must-run experimental story compact. - **MAX_BASELINE_FAMILIES = 3** — Prefer a few strong baselines over many weak ones. - **DEFAULT_SEEDS = 3** — Use 3 seeds when stochastic variance matters and budget allows. ## Wo
- Overview
- Constants
- Workflow
- Phase 0: Load the Proposal Context
- Phase 1: Freeze the Paper Claims
- Phase 2: Build the Experimental Storyline
- Phase 3: Specify Each Experiment Block
- Phase 4: Turn the Plan Into an Execution Order
- Phase 5: Write the Outputs
- Output Protocols
- Key Rules
- Composing with Other Skills
What does the experiment-plan skill do?
Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill experiment-plan-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.