Memory Transfer — Cross-Agent Migration for OpenClaw
Migrate memories, preferences, writing style, and workflow data from any AI assistant into OpenClaw. Zero learning curve — just say where you came from.
Language Rule
All user-facing messages in this skill MUST match the user's language (from USER.md or detected from conversation). The examples below show both English and Chinese variants — pick the one that matches.
Quick Reference
| Source | Method | User Effort |
|---|
| ChatGPT | ZIP data export (auto-parse) | Click export in settings, upload ZIP |
| ChatGPT (alt) | Prompt-guided | Copy prompt → paste result back |
| Claude.ai | Prompt-guided | Copy prompt → paste result back |
| Gemini | Prompt-guided | Copy prompt → paste result back |
| Copilot | Prompt-guided | Copy prompt → paste result back |
| Perplexity | Prompt-guided | Copy prompt → paste result back |
| Claude Code | Auto-scan local files | None |
| Cursor | Auto-scan local files | None |
| Windsurf | Auto-scan local files | None |
Flow
Step 1: Identify Source
Ask the user one question:
EN: Which AI assistant are you coming from?
ZH: 你之前用的是哪个 AI 助手？
If the user already mentioned it (e.g., "I used ChatGPT for a year"), skip this step.
Determine the migration path:
- Cloud AI (ChatGPT, Claude.ai, Gemini, Copilot, Perplexity) → Step 2A or 2B
- Local Agent (Claude Code, Cursor, Windsurf) → Step 2C
Step 2A: ChatGPT ZIP Export (Preferred for ChatGPT)
This is the easiest and most complete method for ChatGPT users.
EN version:
The easiest way — export your ChatGPT data:
- Open ChatGPT → Settings → Data Controls → Export Data
- Click "Export" — you'll receive an email
- Download the ZIP file and send it to me
I'll automatically parse all your conversations, memories, and preferences.
ZH version:
最简单的方式——去 ChatGPT 导出你的数据：
- 打开 ChatGPT → Settings → Data Controls → Export Data
- 点 "Export"，你会收到一封邮件
- 下载 ZIP 文件，直接发给我
我会自动解析你所有的对话记录、记忆和偏好。
When the user uploads the ZIP, run the parser:
node <skill_dir>/scripts/parse-chatgpt-export.js "<path_to_zip>"
The parser outputs a structured JSON to stdout. Read and process it.
If the user doesn't want to wait for the email or prefers a faster method, fall back to Step 2B.
Step 2B: Prompt-Guided Export (All Cloud AIs)
Tell the user to open a new conversation with their old AI and send the export prompt.
Important: Give the prompt in the user's primary language. If the user chats in Chinese, give the Chinese prompt — this ensures the old AI responds in Chinese too, preserving the original context.
EN version — tell the user:
Go to your old AI, start a new chat, and send it this message. Then copy the response back to me.
ZH version — tell the user:
去你之前的 AI 那里，开一个新对话，把下面这段话发给它，然后把回复复制给我。
Export Prompt (English):
I'm migrating to a new AI assistant and need a complete export of everything you know about me. Please provide ALL of the following in a single, well-structured response:
## 1. Stored Memories
List every memory you have stored about me. Output verbatim — do not summarize or paraphrase.
## 2. Custom Instructions
Reproduce my complete custom instructions / personalization settings. If empty, say so.
## 3. Identity & Context
- My name, profession, industry
- Tools and platforms I use regularly
- Languages I work in
## 4. Communication Preferences
- My writing style (tone, sentence length, vocabulary level, quirks)
- How I like information structured and presented
- Formatting preferences (bullet points vs prose, headers, code blocks)
## 5. Behavioral Patterns
- What I ask you to help with most (rank by frequency)
- Recurring projects or workflows
- Strong opinions or preferences I've expressed
- Things I've told you NOT to do — list every correction
## 6. Topics & Interests
- Subjects I discuss frequently
- Areas of expertise
- Curiosities and learning goals
Be exhaustive. Better to include too much than too little. Format as a reference document, not conversational text. This will be directly imported into another AI's memory system.
Export Prompt (中文):
我正在迁移到另一个 AI 助手，需要你把关于我的一切都导出来。请在一次回复中提供以下所有内容，用清晰的结构输出：
## 1. 存储的记忆
列出你存储的关于我的每一条记忆，原文输出，不要总结或改写。
## 2. 自定义指令
完整复现我的自定义指令/偏好设置。如果为空请说明。
## 3. 身份与背景
- 我的姓名、职业、行业
- 我常用的工具和平台
- 我使用的语言
## 4. 沟通偏好
- 我的写作风格（语气、句子长度、词汇水平、表达习惯）
- 我喜欢信息怎么组织和呈现
- 格式偏好（列表还是段落、标题、代码块）
## 5. 行为模式
- 我最常让你帮忙做什么？按频率排序
- 反复出现的项目或工作流
- 我表达过的强烈观点或偏好
- 我纠正过你什么？让你不要做什么？列出所有"别这样"的模式
## 6. 话题与兴趣
- 我经常讨论的话题
- 我的专业领域
- 我的好奇心和学习目标
尽可能详尽，宁可多不可少。用参考文档格式输出，不要用对话体。这些内容将直接导入另一个 AI 的记忆系统。
When the user pastes the result back, proceed to Step 3.
Step 2C: Local Agent Auto-Scan
For local agents, scan files automatically. No user action needed.
Claude Code:
# Global config
cat ~/.claude/CLAUDE.md 2>/dev/null
# All project memories
find ~/.claude/projects -name "*.md" -path "*/memory/*" 2>/dev/null | head -20 | while read f; do
echo "=== $f ==="
cat "$f"
done
# Project instructions
find ~/.claude/projects -name "CLAUDE.md" 2>/dev/null | head -20 | while read f; do
echo "=== $f ==="
cat "$f"
done
Cursor:
cat ~/.cursor/rules/*.md 2>/dev/null
find . -maxdepth 3 -name ".cursorrules" 2>/dev/null | head -10 | while read f; do
echo "=== $f ==="
cat "$f"
done
Windsurf:
cat ~/.windsurf/rules/*.md 2>/dev/null
find . -maxdepth 3 -name ".windsurfrules" 2>/dev/null | head -10 | while read f; do
echo "=== $f ==="
cat "$f"
done
Generic (AGENT.md / CLAUDE.md / rules files):
find ~ -maxdepth 4 \( -name "AGENT.md" -o -name "CLAUDE.md" -o -name ".cursorrules" -o -name ".windsurfrules" \) 2>/dev/null | head -20 | while read f; do
echo "=== $f ==="
cat "$f"
done
After scanning, present what was found and proceed to Step 3.
Step 3: Parse & Categorize
Process the imported data (whether from ZIP, prompt response, or local scan) into these categories:
KEEP:
- Identity (name, profession, industry, language)
- Writing style and communication preferences
- Tools, platforms, tech stack
- Active projects and workflows
- Structural preferences (how to organize/present info)
- "Don't do this" rules and corrections
- Domain knowledge and expertise areas
- Behavioral patterns and habits
FILTER OUT:
- Completed one-off tasks
- Outdated context (finished projects, old deadlines)
- Source-specific references ("as a ChatGPT user...")
- API keys, tokens, passwords — never migrate credentials
- Hallucinated or inaccurate memories (flag suspicious ones)
- Duplicate or redundant entries
Step 4: Review & Confirm
Present the cleaned data to the user, organized by destination:
EN:
📋 Migration Preview
Writing to USER.md (your profile):
- Name: ...
- Profession: ...
- Language: ...
- Communication style: ...
Writing to MEMORY.md (long-term memory):
- [project/knowledge/experience entries...]
Writing to TOOLS.md (tool preferences):
- Tools: ...
- Platforms: ...
Anything to change? I'll write it once you confirm.
ZH:
📋 迁移预览
写入 USER.md（你的画像）：
- 姓名：...
- 职业：...
- 语言偏好：...
- 沟通风格：...
写入 MEMORY.md（长期记忆）：
写入 TOOLS.md（工具偏好）：
有什么要改的吗？确认后我就写入。
Wait for user confirmation. They can:
- Approve all
- Remove specific items
- Edit entries
- Add things that were missed
Step 5: Write to Memory System
After confirmation, write to the appropriate files:
USER.md — Identity, communication preferences, language, timezone
MEMORY.md — Knowledge, projects, experience, behavioral patterns
TOOLS.md — Tools, platforms, environment-specific notes
Rules for writing:
- Merge, don't overwrite — if these files already have content, integrate new data with existing
- Preserve structure — follow the existing format of each file
- Add a migration note — append a comment like
<!-- Migrated from ChatGPT on 2026-03-30 -->
- Use the user's language — write entries in the language the user communicates in
Step 6: Verify
After writing, confirm:
EN:
✅ Migration complete!
Here's what I now know about you:
[Brief summary of key imported info]
This info is now in my memory system — I'll use it naturally in our conversations.
Feel free to tell me if anything needs updating.
ZH:
✅ 迁移完成！
现在我知道的关于你的事：
[Brief summary of key imported info]
这些信息已经写入我的记忆系统，以后的对话中我会自然地使用它们。
随时可以告诉我补充或修正任何内容。
Special Cases
Multiple Sources
If the user used several AI assistants, handle them sequentially. Deduplicate across sources before writing.
Partial Migration
User might say "just bring over my writing preferences" — respect scope limits. Only migrate what they want.
Conflict Resolution
If imported data conflicts with existing memory (e.g., different profession noted), ask the user which is current.
Re-migration
If the user runs migration again later, merge new data with existing. Don't create duplicates.
Platform-Specific Notes
ChatGPT Data Export ZIP Structure
├── conversations.json ← Main conversation history
├── model_comparisons.json ← Model comparison data
├── message_feedback.json ← Thumbs up/down data
├── shared_conversations.json
├── user.json ← Account info
└── chat.html ← Rendered conversations
The parser (scripts/parse-chatgpt-export.js) extracts:
- User messages patterns and topics
- Correction patterns (user said "no, I meant...")
- Frequently discussed subjects
- Writing style from user messages
- Tool/platform mentions (word-boundary-aware detection)
- Project references
Claude.ai
Users can access their memory at claude.ai → Settings → Memory. They can either:
- Use the prompt method (Step 2B)
- Manually copy their memory entries
Gemini
Gemini stores "Saved Info" in Settings. Prompt method works best.
Copilot
Limited memory capabilities. Prompt method captures what's available.
Security
- NEVER migrate API keys, tokens, or credentials
- Warn user if imported text contains what looks like secrets (regex:
/(?:sk-|ghp_|token|password|secret|key)\s*[:=]/i)
- All imported data is shown to user before writing — no silent imports
- ZIP files are processed in temp directory with path traversal protection, cleaned up after
