experiment-plan

Translate research proposals into claim-driven experimental plans with run order and evaluation protocol.

Updated Apr 2, 2026
One-click install
npx skills add https://github.com/dz306271098/ARIS_for_Robotics --skill experiment-plan-dz306271098
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: experiment-plan
Source: https://github.com/dz306271098/ARIS_for_Robotics/tree/main/skills/experiment-plan
Command: npx skills add https://github.com/dz306271098/ARIS_for_Robotics --skill experiment-plan-dz306271098

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps researchers convert a method idea into a concrete, claim-driven experiment roadmap that can be executed with a clear run order and evaluation plan.

Core Features & Use Cases

  • Build an end-to-end experimental plan from a research proposal, including primary and secondary claims, datasets, baselines, metrics, and milestones.
  • Generate a compact execution order with sanity checks, baselines, and risk mitigation strategies to streamline project planning.
  • Provide executable templates compatible with structured review workflows and adversarial checks to ensure robust evaluation planning.

Quick Start

Provide a concise research idea or claim to generate a complete experiment plan with blocks, baselines, metrics, and a run order.

Frequently Asked Questions about experiment-plan

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

FAQPage Schema
How do I turn a research proposal into a structured experiment plan with baselines and metrics?

To create a structured experiment plan, provide a concise research proposal to generate a claim-driven roadmap with explicit run order, evaluation protocol, baselines, and metrics.

What is claim-driven experiment planning and when do I need it?

Claim-driven experiment planning restricts primary claims to enforce compact scope, specifying datasets, seeds, and success criteria to ensure reproducibility when defending core research claims.

How do I design an execution run order for machine learning experiments?

Generate a compact execution run order by incorporating sanity checks, baselines, and risk mitigation strategies to streamline project planning and ensure robust evaluation.

Can I use this experiment planning approach for adversarial checks and structured review workflows?

Yes, this approach provides executable templates compatible with structured review workflows and adversarial checks to ensure robust evaluation planning for your experiments.

Does this experiment planning method enforce reproducibility for research claims?

Yes, reproducibility is enforced by restricting the number of primary claims and explicitly specifying datasets, seeds, and success criteria within the experimental plan.

What's the best way to define compute budget and success criteria for research experiments?

Define compute budget and success criteria by translating your research method idea into a structured experimental plan that explicitly specifies these constraints for reproducibility.