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plan-experiment

Official

Turn a research idea into a runnable plan.

Education & Research#research planning#mechanistic interpretability#session workflow#causal abstraction#hydra configs#experiment DAG#cache reuse
Authorgoodfire-ai
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill converts a fuzzy research goal into a complete experiment plan, defining the causal task setup and the full analysis dependency DAG so downstream execution and interpretation can run reliably.

Core Features & Use Cases

  • Objective crystallization: Produces a structured RESEARCH_OBJECTIVE.md with an evidence-oriented objective, optional hypotheses, and success criteria.
  • Dependency-DAG planning: Builds PLAN.md with the analysis chain (baseline → locate → subspace → activation/manifold geometry checks, etc.), including per-node I/O contracts and measurable pre-flight gates.
  • Runner configuration strategy: Specifies how to materialize runner configs for /run-experiment, including sweep and cache-reuse considerations to reduce redundant compute.

Quick Start

Start a new research investigation by running plan-experiment to generate the session plan artifacts that you will execute next with /run-experiment.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: plan-experiment
Download link: https://github.com/goodfire-ai/causalab/archive/main.zip#plan-experiment

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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