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Session History

Search and browse past conversation history across all sessions. Use when recalling prior work, finding old discussions, resuming dropped threads, or when th...

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版本1.0.0
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name: session-history description: Search and browse past conversation history across all sessions. Use when recalling prior work, finding old discussions, resuming dropped threads, or when the user references something from a previous conversation that isn't in memory files. Also use when asked to "remember" something discussed before, find "that conversation about X", or continue work from a past session.

Session History

Search through past OpenClaw session transcripts (JSONL files in ~/.openclaw/agents/*/sessions/).

Quick Reference

# Search for conversations about a topic
python3 scripts/search_sessions.py "gclid pipeline error"

# List recent sessions
python3 scripts/search_sessions.py --list --days 3

# Search specific agent's history
python3 scripts/search_sessions.py "flight monitor" --agent main

# Wider time range
python3 scripts/search_sessions.py "quantum encryption" --days 30 --max-results 5

Workflow

  1. Run search_sessions.py with the user's query terms to find relevant sessions
  2. Use sessions_history tool with the sessionKey to pull full context from a match
  3. If sessions_history doesn't work (old/closed sessions), read the JSONL file directly with read
  4. Summarize what was found — don't dump raw transcripts

When to Use

  • User says "remember when we discussed X?" or "we talked about Y last week"
  • Resuming a thread that isn't captured in memory files
  • Finding a decision, code snippet, or error from a past session
  • Cross-referencing what was said vs what's in MEMORY.md

Tips

  • Also check memory_search first — it indexes session transcripts too
  • Combine both: memory_search for semantic matching, search_sessions.py for keyword/exact matching
  • The script searches user AND assistant messages
  • JSONL path format: ~/.openclaw/agents/{agent_id}/sessions/{session_uuid}.jsonl

如何使用「Session History」?

  1. 打开小龙虾AI(Web 或 iOS App)
  2. 点击上方「立即使用」按钮,或在对话框中输入任务描述
  3. 小龙虾AI 会自动匹配并调用「Session History」技能完成任务
  4. 结果即时呈现,支持继续对话优化

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