data-analysis

name	data-analysis
description	Analyze structured datasets (CSV, databases, numerical data). Triggers on 'analyze data', 'compute statistics', 'find patterns in data'. NOT for qualitative research — use research/analysis.
allowed-tools	Bash, Read, Write

When to Use

• Computing descriptive statistics on structured data (CSV, TSV, databases)
• Identifying trends, correlations, or anomalies in numerical datasets
• Testing hypotheses with data evidence
• Segmenting or grouping records by attributes

When NOT to Use

• Qualitative or literature-based research analysis — use research/analysis
• Data has not been cleaned yet — use data-cleaning first
• You need charts or visual output — use visualization
• You need a formatted report — use reporting

Instructions

1. Load the dataset specified in $ARGUMENTS. Confirm the file exists and inspect its schema (columns, types, row count).
2. Compute descriptive statistics:
   • Central tendency: mean, median, mode for numeric columns
   • Spread: standard deviation, min, max, percentiles
   • Counts and frequencies for categorical columns
3. Identify patterns:
   • Compute correlations between numeric variables
   • Detect trends over time-series data (if timestamps present)
   • Flag anomalies or outliers (values beyond 2-3 standard deviations)
4. Test hypotheses if specified in $ARGUMENTS:
   • State the hypothesis clearly
   • Select appropriate test (t-test, chi-square, regression)
   • Report results with confidence levels
5. Segment the data if grouping criteria are specified:
   • Group by relevant dimensions
   • Compare metrics across segments
6. Summarize findings with supporting evidence (specific numbers, not vague claims).

Output

## Analysis Results

### Dataset Overview
- Records: [count]
- Period: [date range if applicable]
- Key columns: [list]

### Key Metrics
| Metric | Value | Notes |
|--------|-------|-------|
| ... | ... | ... |

### Findings
1. **[Finding]**: [Evidence with numbers]
2. **[Finding]**: [Evidence with numbers]

### Correlations
- [variable A] <-> [variable B]: [coefficient]

### Anomalies
- [description with specific values]