experiment-plan

Generate claim-driven experiment roadmaps with ablation matrices and run order.

Updated Apr 21, 2026
One-click install
npx skills add https://github.com/Shallow-W/llm-wiki --skill experiment-plan-shallow-w
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: experiment-plan
Source: https://github.com/Shallow-W/llm-wiki/tree/main/.claude/skills/experiment-plan
Command: npx skills add https://github.com/Shallow-W/llm-wiki --skill experiment-plan-shallow-w

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It converts a refined research idea or method into a structured, claim-driven set of experiments that a reviewer would accept as sufficient to validate novelty, simplicity, and the true contribution of any frontier component.

Core Features & Use Cases

  • Claim freezing into a defensible map: Produces primary/supporting claims, anti-claims to rule out, and the minimum convincing evidence required for each claim.
  • Paper-ready experiment storyline: Chooses a compact set of experimental blocks (main anchor result, novelty isolation, simplicity check, frontier necessity check, and failure/diagnostic work) and assigns priority as MUST-RUN or NICE-TO-HAVE.
  • Execution-ready run order and budgets: Produces an ordered milestone plan with compute/cost estimates and stop/go decision gates, plus output files for the plan and an experiment tracker.

Quick Start

Ask for a detailed experiment plan by saying: "Create a paper-ready, claim-driven experiment roadmap for my method, including ablations, evaluation protocol, run order, and compute-budget assumptions."

Frequently Asked Questions about experiment-plan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I plan experiments for a research paper to satisfy reviewer validation?▼

To plan experiments for a research paper, you generate a claim-driven experiment roadmap mapping primary claims, anti-claims, and minimum convincing evidence into a reviewer-acceptable validation sequence with priority blocks.

What is the best way to design an ablation study matrix for LLM or diffusion models?▼

Designing an ablation study matrix requires isolating novelty and checking frontier necessity within your experiment roadmap, organizing runs into MUST-RUN or NICE-TO-HAVE priority blocks for your LLM or diffusion models.

How do I estimate compute budget and run order for machine learning experiments?▼

Estimating compute budget and run order involves generating an ordered milestone plan with cost estimates and stop/go decision gates, ensuring budget-aware execution for your machine learning experiments.

Can I generate an evaluation protocol from a refined research proposal?▼

Yes, you can generate an evaluation protocol from a refined research proposal by deriving the problem anchor and contribution, then freezing them into a defensible map of primary and supporting claims.

Does this approach support RL-based contributions and reinforcement learning evaluation?▼

Yes, this approach supports RL-based contributions by tailoring the experiment storyline and evaluation protocol to validate novelty, simplicity, and the true contribution of frontier reinforcement learning components.