Chatgpt Memory Extraction

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name: chatgpt-memory-extraction description: "Extract structured personal memories from ChatGPT export data (conversations JSON). Produces organized timeline, people profiles, and thematic records by deeply reading every conversation. Use when: (1) user exported or wants to export ChatGPT data, (2) user wants to organize/analyze/search their chat history, (3) user wants to build a personal memory archive or diary from conversations, (4) user asks to extract people/events/emotions/knowledge/timeline from ChatGPT, (5) user mentions conversations.json or ChatGPT data export, (6) user wants to migrate memories from ChatGPT to another system, (7) user wants a summary or review of their ChatGPT usage over time. Triggers on: 'organize my ChatGPT history', 'extract memories from ChatGPT', 'analyze my ChatGPT export', '整理ChatGPT对话', '导出ChatGPT数据', 'build memory from chats', 'what did I talk about with ChatGPT', 'review my ChatGPT conversations', 'make a timeline from my chats', 'ChatGPTのデータを整理'. NOT for: other AI chat exports (Claude/Gemini), real-time logging, or automated summarization without human review."

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ChatGPT Memory Extraction

Transform ChatGPT conversation exports into a structured personal memory archive.

⚠️ For Users

AI agents cut corners on large text volumes. Review each batch. Praise quality, not speed.

Read quality rules for ChatGPT-specific pitfalls and known AI failure modes.

Workflow

1. Prepare: User exports ChatGPT data: - Go to ChatGPT → Settings → Data controls → Export data → Confirm export - OpenAI will send an email when the export is ready (may take hours to days depending on data size) - Download the zip file from the email link (requires being logged into ChatGPT) - Unzip to get conversations-*.json files and other data 2. Extract: Run scripts/extract_conversations.py to convert JSON → readable text files + conversation index 3. Read & Write: Process one quarter at a time. Read every conversation fully. Write timeline per output-format.md. User reviews before proceeding. Split into monthly batches for 100+ conversations. 4. Extract Dimensions: Update people files and topic files. Every person mentioned → their file updated. 5. Incremental: On new exports, compare IDs, process only new content.

Output Structure

See output-format.md.