Dataset README Generator
Create a polished README.md for your datasets so teams can understand columns, preview rows, and start querying faster.
Quick Start
- 1Upload your dataset
Drop a CSV, Parquet, or JSON file to parse schema and sample rows.
- 2Customize README sections
Adjust project context, data dictionary notes, and usage details.
- 3Copy and publish
Export a polished README.md with table structures and share-ready copy.
Specs
- Input formats
- CSV, Parquet, JSON
- Output format
- README.md
- Processing
- Client-side
Data stays on your device
All processing runs locally in your browser. Your data is not uploaded.
Generate clear, standardized documentation for datasets in seconds. Share schema details, sample rows, and onboarding context so teammates can use your data faster.
3
Supported formats
Markdown
Output
0 bytes
Data transmitted
Automatic Schema Summary
Extract field names and types directly from your dataset for clean documentation tables.
Sample Rows Included
Include representative records to help collaborators understand structure and content quickly.
Ready for Repositories
Copy Markdown output directly into GitHub, GitLab, Notion, or internal documentation portals.
Privacy First
The tool runs in-browser so sensitive datasets stay on your machine.
What file formats does this README generator support?
You can generate a README from CSV, Parquet, and JSON datasets. The tool infers schema and sample data from your file.
Is my dataset uploaded to a server?
No. Processing runs in your browser so your dataset stays on your device.
Can I use the output in GitHub repositories?
Yes. The generated Markdown is compatible with GitHub README files and can be pasted directly into your repo.
What should a dataset README include?
A strong README includes dataset purpose, schema descriptions, sample records, update cadence, and usage notes.