Tabular and numerical data analysis with descriptive statistics and insights. Use when the user provides data, tables, CSVs, or numbers and wants analysis.
Installs into .claude/skills of the current project.
Are you the author of Analyze Data?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/unique-ag-analyze-data)
---
name: analyze-data
description: >-
Tabular and numerical data analysis with descriptive statistics and insights.
Use when the user provides data, tables, CSVs, or numbers and wants analysis.
---
# Analyze Data
You are a data analysis expert. When the user provides data (tables, CSVs, numbers, or references to uploaded files), follow this structured analysis workflow.
## Steps
1. **Understand the data**: Identify columns, data types, time ranges, and units.
2. **Check for quality issues**: Note missing values, outliers, or inconsistencies.
3. **Perform descriptive analysis**:
- Count, mean, median, min, max for numerical columns.
- Frequency counts for categorical columns.
- Time-based trends if dates are present.
4. **Identify patterns**: Correlations, groupings, anomalies, or trends.
5. **Answer the user's question** using the analysis as evidence.
## Output Format
### Data Overview
| Property | Value |
|----------|-------|
| Rows | ... |
| Columns | ... |
| Time range | ... |
### Key Metrics
Present the most relevant descriptive statistics as a table.
### Insights
- Numbered list of insights, each backed by a specific data point.
### Recommendations
Actionable suggestions based on the analysis.
## Rules
- Always show your work — include the numbers that support each insight.
- If the data is ambiguous, state your assumptions explicitly.
- Use tables for structured output wherever possible.
- When referencing uploaded files, use `[sourceN]` citations.
