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dataclaw

Export AI coding conversations to Hugging Face datasets

Exports Claude Code, Codex, and other coding-agent conversation history into structured datasets for Hugging Face. Redacts secrets, emails, usernames, and PII automatically so private data never leaks into public datasets. Guides users through a gated review-and-confirm flow before anything is published, removing guesswork and manual cleanup.
npx skills add peteromallet/dataclaw --all -g -y
Available:

Instructs the AI agent to follow each dataclaw command's JSON next_steps through a gated six-stage flow of prep, local export, PII audit, confirmation, and publishing to Hugging Face.

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Frequently Asked Questions

FAQPage Schema
How to install DataClaw?โ–ผ

Run `npx skills add peteromallet/dataclaw --all -g -y` in your terminal to install the skill globally for your AI agent.

How to export Claude Code conversations to Hugging Face?โ–ผ

DataClaw parses your Claude Code and Codex session logs, redacts sensitive data, and uploads the result as a ready-to-use Hugging Face dataset with one command.

Does DataClaw remove secrets and personal data?โ–ผ

Yes. It redacts API keys, tokens, emails, usernames, and custom strings, then requires a manual PII review and confirmation step before anything can be published.

Which AI coding agents does DataClaw support?โ–ผ

It includes parsers for Claude Code, Codex, Cursor, Gemini, Kimi, OpenClaw, and other coding agents, all exporting to the same dataset format.

Can I review my data before publishing?โ–ผ

Yes. Publishing is gated: you must export locally, run a PII audit, and confirm with attestations before the push command will work.

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