One-click install
npx skills add https://github.com/goodfire-ai/causalab --skill interpret-experiment
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: interpret-experiment
Source: https://github.com/goodfire-ai/causalab/tree/main/.claude/skills/interpret-experiment
Command: npx skills add https://github.com/goodfire-ai/causalab --skill interpret-experiment

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It prevents research results from being hard to summarize by automatically converting an experiment plan plus produced artifacts into a single, evidence-grounded report.

Core Features & Use Cases

  • Plan-to-evidence scoring: Extracts objective, success criteria, and hypotheses from the session plan, then matches them to shipped and session-local analysis outputs.
  • Artifact-aware interpretation: Discovers what actually ran from resolved configs and on-disk artifacts, including session-local methods and analyses, and records plan-vs-reality gaps.
  • Optional paper comparison: When replication context is present, compares key metrics against the paper’s reported findings and annotates discrepancy categories.
  • Figure embedding and structured output: Copies/symlinks curated figures into the session result folder and writes a consistent result/REPORT.md, while logging issues separately.

Quick Start

Run the experiment with /run-experiment, then invoke interpret-experiment (or let it auto-run) to generate ${SESSION_DIR}/result/REPORT.md from the plan and artifacts.

Frequently Asked Questions about interpret-experiment

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

FAQPage Schema
How do I generate an automated analysis report from experiment runs?▼

You can generate an automated analysis report by matching a planned objective, success criteria, and hypotheses to produced artifacts from a completed experiment session. It reads session markers, plan files, and resolved runner configs to create a consolidated result.

What is mechanistic interpretability experiment interpretation?▼

Mechanistic interpretability experiment interpretation is the process of converting a causal abstraction research plan plus produced artifacts into a single, evidence-grounded report that scores hypotheses against actual analysis outputs.

How do I compare my research results against a replication paper?▼

You can compare results against a replication paper by providing optional paper context during experiment interpretation. The tool compares key metrics against the paper's reported findings and annotates discrepancy categories in the final report.

Can I embed figures into research reporting outputs automatically?▼

Yes, automated research reporting can embed figures by copying or symlinking curated figures into the session result folder. It then writes a consistent REPORT.md file with the figures embedded directly.

What happens when my experiment plan does not match produced artifacts?▼

When an experiment plan does not match produced artifacts, the interpretation process records plan-vs-reality gaps. It discovers what actually ran from on-disk artifacts and logs these issues separately from the main report.

Do I need to use run-experiment before generating an experiment report?▼

Yes, you need a completed run-experiment session before generating an experiment report. The reporting tool applies to completed sessions and reads session markers, plan files, and resolved runner configurations to function correctly.