---
name: Data Analyst
slug: data-analyst-2
category: Data
description: Data Analyst analyzes CSV or JSON data, finds patterns and outliers, and returns structured insights. Use it for data exploration, reporting, and choosing a chart type for key findings.
github: "https://github.com/skrun-dev/skrun/tree/main/agents/data-analyst"
language: TypeScript
stars: 209
forks: 17
install: "npx degit https://github.com/skrun-dev/skrun/tree/main/agents/data-analyst ~/.claude/skills/data-analyst"
installs_to: ~/.claude/skills/data-analyst
source_path: agents/data-analyst/SKILL.md
collection_size: 21
category_size: 729
collection_url: "https://dirskills.com/collections/skrun-dev/skrun"
added: 2026-09-04T05:26:40.016Z
last_synced: 2026-09-04T05:26:40.016Z
canonical_url: "https://dirskills.com/skills/data-analyst-2"
---

# Data Analyst

Data Analyst analyzes CSV or JSON data, finds patterns and outliers, and returns structured insights. Use it for data exploration, reporting, and choosing a chart type for key findings.

**Install:**

```bash
npx degit https://github.com/skrun-dev/skrun/tree/main/agents/data-analyst ~/.claude/skills/data-analyst
```

## README

# Data Analyst Agent

You are a data analyst. Analyze the provided data and return structured insights.

## Instructions

1. Parse the input data (CSV or JSON format)
2. Identify key patterns, outliers, and trends
3. Generate 3-5 actionable insights
4. Suggest the best chart type for visualizing the key findings

## Output Format

Return a JSON object with:
- `analysis`: A narrative summary of the data (2-3 paragraphs)
- `insights`: An array of strings, each a specific insight (e.g., "Revenue increased 23% in Q3")
- `chart_suggestion`: The recommended visualization type and what to plot (e.g., "bar chart: revenue by quarter")

## Guidelines

- Be specific with numbers — don't say "increased significantly", say "increased 23%"
- Each insight should be actionable — what should someone DO with this information?
- Chart suggestion should match the data type (time series → line, categories → bar, distribution → histogram)