Overview
- Skill Key
- amor71/session-history
- Author
- amor71
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/amor71/session-history
- Latest Commit SHA
- ad2491ca50be7f5e139a9e11b5947fb3de9249a5
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.
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Status
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 session-history 技能。 若已安装,则直接安装 session-history 技能。
# Session History
Search through past OpenClaw session transcripts (JSONL files in `~/.openclaw/agents/*/sessions/`).
## Quick Reference
```bash
# 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`
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