# experiment-plan

This skill turns a refined research idea into a claim-driven experiment roadmap with ablations and run order. Use it before implementation or paper validation.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 544 installs · ★ 18090
- Author: wanshuiyin
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/HEAD/skills/experiment-plan/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/experiment-plan

## What it does

\`experiment-plan` turns a refined research proposal or method idea into an experiment roadmap. It freezes the primary and supporting claims, adds an anti-claim to test, and connects each claim to the evidence a reviewer would need. The planned story can cover the main result, novelty isolation, a simplicity check, frontier-component necessity, and failure analysis.

The workflow moves from sanity checks and baseline reproduction to the final method, decisive ablations, and optional polish. Each kept block gets a dataset or task, compared systems, metrics, setup details, success criteria, failure interpretation, and a paper placement target. The skill can read and edit files, run `Bash`, and use `WebSearch` or `WebFetch`. One practical constraint follows from the workflow: give it the problem and compute limits early, because those facts shape the run order and budget.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-plan -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/experiment-plan/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/experiment-plan/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-plan -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/experiment-plan/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-plan -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/experiment-plan/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install wanshuiyin/Auto-claude-code-research-in-sleep experiment-plan
```

2. **Manually: put the files in place**
- File: `.github/skills/experiment-plan/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-plan -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --path skills/experiment-plan
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/experiment-plan/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill experiment-plan -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/HEAD/skills/experiment-plan/SKILL.md

## When to use it
- turn a research proposal into an experiment roadmap
- separate the main contribution from supporting claims
- design an ablation matrix and baseline set
- order runs with decision gates and compute limits
- test whether an LLM, VLM, Diffusion, or RL component is necessary

## Example prompts
- Turn this research idea into a detailed experiment plan with primary claims, baselines, ablations, metrics, and run order.
- After `research-refine`, design paper-ready validation with datasets, compute budget, success criteria, and failure interpretations.
- Plan experiments for a method with an LLM component and separate must-run checks from appendix experiments.

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 641732192bbb8fd5.

BEGIN THIRD-PARTY FILE 641732192bbb8fd5
```text
---
name: experiment-plan
description: '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.'
allowed-tools: Bash(*), Read, Write, Edit, Grep, Glob, WebSearch, WebFetch
---

# 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.

## Workflow

### Phase 0: Load the Proposal Context

Read the most relevant existing files first if they exist:

- `refine-logs/FINAL_PROPOSAL.md`
- `refine-logs/REVIEW_SUMMARY.md`
- `refine-logs/REFINEMENT_REPORT.md`

Extract:

- **Problem Anchor**
- **Dominant contribution**
- **Optional supporting contribution**
- **Critical reviewer concerns**
- **Data / compute / timeline constraints**
- **Which frontier primitive is central, if any**

If these files do not exist, derive the same information from the user's prompt.

### Phase 1: Freeze the Paper Claims

Before proposing experiments, write down the claims that must be defended.

Use this structure:

- **Primary claim**: the main mechanism-level contribution
```
END THIRD-PARTY FILE 641732192bbb8fd5

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First 2434 of 9728 bytes. © wanshuiyin · MIT · https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/HEAD/skills/experiment-plan/SKILL.md

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