How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/wanshuiyin/auto-claude-code-research-in-sleep --skill analyze-resultsBefore you start
- Installation does not include a model subscription, API allowance or permission to access your files.
- Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
Analyze Experiment Results
Analyze: $ARGUMENTS
Workflow
Step 1: Locate Results
Find all relevant JSON/CSV result files:
- Check
figures/,results/, or project-specific output directories - Parse JSON results into structured data
Step 2: Build Comparison Table
Organize results by:
- Independent variables: model type, hyperparameters, data config
- Dependent variables: primary metric (e.g., perplexity, accuracy, loss), secondary metrics
- Delta vs baseline: always compute relative improvement
Step 3: Statistical Analysis
- If multiple seeds: report mean +/- std, check reproducibility
- If sweeping a parameter: identify trends (monotonic, U-shaped, plateau)
- Flag outliers or suspicious results
Step 4: Generate Insights
For each finding, structure as:
- Observation: what the data shows (with numbers)
- Interpretation: why this might be happening
- Implication: what this means for the research question
- Next step: what experiment would test the interpretation
Step 5: Update Documentation
If findings are significant:
- Propose updates to project notes or experiment reports
- Draft a concise finding statement (1-2 sentences)
Output Format
Always include:
- Raw data table
- Key findings (numbered, concise)
- Suggested next experiments (if any)
