analyze-results

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Translated

Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.

4installs

Sourcewanshuiyin/auto-claude-code-research-in-sleep

Added on2026-03-16

NPX Install

npx skill4agent add wanshuiyin/auto-claude-code-research-in-sleep analyze-results

SKILL.md Content

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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)