| 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:
-
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.
-
Run analysis script:
PYTHONPATH=. python exp/{current_exp}/analyze.py
This generates exp/{current_exp}/results/summary.md.
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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.
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Merge interpretation into exp/{current_exp}/README.md under the "## Findings" section.
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Update exp/summary.md cross-experiment table: update the row for current_exp with status "Analyzed" and key finding summary (one line).
-
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."
-
Advance pipeline state:
- Set
stage to "analysis" in .pipeline-state.json
-
Print summary of generated artifacts:
exp/{current_exp}/results/summary.md — quantitative analysisexp/{current_exp}/README.md — updated with findingsslides/{current_exp}-analysis.html — presentation (generating in background)
