peteromallet/dataclaw

• highreadme#1

  Reposition the core technical description in the README

  Why:

  CURRENT

  # DataClaw
  
  > **This is a performance art project.** Anthropic built their models on the world's freely shared information, then introduced increasingly dystopian data policies to stop anyone else from doing the same with their data - pulling up the ladder behind them. DataClaw lets you throw the ladder back down. The dataset it produces is yours to share.
  
  Turn your Claude Code, Codex, and other coding-agent conversation history into structured data and publish it to Hugging Face with a single command. DataClaw parses session logs, redacts secrets and PII, and uploads the result as a ready-to-use dataset.

  COPY-PASTE FIX

  Copy

  # DataClaw
  
  Turn your Claude Code, Codex, and other coding-agent conversation history into structured data and publish it to Hugging Face with a single command. DataClaw parses session logs, redacts secrets and PII, and uploads the result as a ready-to-use dataset.
  
  > **This is also a performance art project.** Anthropic built their models on the world's freely shared information, then introduced increasingly dystopian data policies to stop anyone else from doing the same with their data - pulling up the ladder behind them. DataClaw lets you throw the ladder back down. The dataset it produces is yours to share.

  OpenDoneDismiss
• hightopics#2

  Add relevant topics to the repository

  Why:

  COPY-PASTE FIX

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  ai-assistants, conversation-history, dataset-generation, huggingface, claude-ai, codex, data-export, privacy, open-data, macos-app

  OpenDoneDismiss
• mediumhomepage#3

  Add the project's homepage URL

  Why:

  COPY-PASTE FIX

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  https://github.com/peteromallet/dataclaw

  OpenDoneDismiss

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

  How can I export and share my AI coding assistant conversation history as structured data?

  you: not recommended
  AI recommended (in order):

  1. VS Code
  2. Sublime Text
  3. Notepad++
  4. Google Docs
  5. Microsoft Word
  6. Chrome
  7. Firefox
  8. Edge
  9. Python
  10. Beautiful Soup
  11. ChatGPT
  12. Google Gemini
  13. GitHub Copilot Chat
  14. Selenium
  15. Playwright
  16. OpenAI's API

  AI recommended 16 alternatives but never named peteromallet/dataclaw. This is the gap to close.

  Show full AI answer
• CATEGORY QUERY

  Tool to anonymize and publish my coding AI interactions as a public dataset?

  you: not recommended
  AI recommended (in order):

  1. Pandas (pandas-dev/pandas)
  2. NLTK (nltk/nltk)
  3. spaCy (explosion/spaCy)
  4. Faker (joke2k/faker)
  5. Regular Expressions (re module)
  6. Presidio (Microsoft/Presidio)
  7. Google Cloud Data Loss Prevention (DLP) API
  8. Amazon Macie
  9. anonypy

  AI recommended 9 alternatives but never named peteromallet/dataclaw. This is the gap to close.

  Show full AI answer

• Metadata completeness

  warn

  Suggestion:

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of peteromallet/dataclaw?

  pass
  ⚠AI did not name peteromallet/dataclaw — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• If a team adopts peteromallet/dataclaw in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI named peteromallet/dataclaw explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• In one sentence, what problem does the repo peteromallet/dataclaw solve, and who is the primary audience?

  pass
  ✓AI named peteromallet/dataclaw explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?