github-featured/wanshuiyin--auto-claude-code-research-in-sleep

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thejesh23 e67ae16294 fix: quote argument-hint YAML values so Copilot CLI ≥1.0.65 loads all skills

`argument-hint: [foo]` YAML-parses as a flow sequence (array), not a
string. Downstream slash-command loaders that validate `argument-hint`
as a string — notably GitHub Copilot CLI ≥ 1.0.65 — silently reject
the skill on load, and the command disappears from the CLI menu.

Wrap the value in double quotes so it parses as a string. No behaviour
change on Claude Code.

2026-07-13 10:23:48 +08:00

1.6 KiB

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name, description, argument-hint, allowed-tools

name	description	argument-hint	allowed-tools
analyze-results	Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.	[results-path-or-description]	Bash(*), Read, Grep, Glob, Write, Edit

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)

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