analyze-experiment

name	analyze-experiment
description	Use when an experiment has completed and results need analysis, interpretation, or presentation. Triggers on "analyze results", "分析实验", "interpret experiment", "what did exp find", "run analysis".
disable-model-invocation	true

Analyze Experiment

Full analysis pipeline for the current experiment.

Instructions

When this skill is invoked:

1. Read pipeline state:

   import json
   state = json.load(open('.pipeline-state.json'))
   current_exp = state['current_exp']
   

   If current_exp is null, ask user which experiment to analyze.

2. Run analysis script:

   PYTHONPATH=. python exp/{current_exp}/analyze.py
   

   This generates exp/{current_exp}/results/summary.md.

3. Delegate to @domain-expert for interpretation:

   Tell it:

   Analyze experiment {current_exp}: Read exp/{current_exp}/results/summary.md for quantitative results. Read exp/{current_exp}/README.md for experiment context. Scan docs/papers/ for relevant domain papers. Provide ~500 word domain interpretation with paper citations.

   domain-expert has memory: project, so it remembers papers from previous sessions.

4. Merge interpretation into exp/{current_exp}/README.md under the "## Findings" section.

5. Update exp/summary.md cross-experiment table: update the row for current_exp with status "Analyzed" and key finding summary (one line).

6. Delegate to @slides-maker for presentation:

   Tell it:

   mode: analysis exp_id: {current_exp} Generate: slides/{current_exp}-analysis.html

   slides-maker has background: true, so it runs in the background. Tell user: "slides-maker is generating slides in the background. You'll be notified when done."

7. Advance pipeline state:

   • Set stage to "analysis" in .pipeline-state.json

8. Print summary of generated artifacts:

   • exp/{current_exp}/results/summary.md — quantitative analysis
   • exp/{current_exp}/README.md — updated with findings
   • slides/{current_exp}-analysis.html — presentation (generating in background)