Search and analyze JSONL conversation logs using jq and rg.
npx skills add https://github.com/lemonlqf/openclaw-rtsp --skill session-logs-lemonlqf
Please help me install this Agent Skill. Skill: session-logs Source: https://github.com/lemonlqf/openclaw-rtsp/tree/main/skills/session-logs Command: npx skills add https://github.com/lemonlqf/openclaw-rtsp --skill session-logs-lemonlqf
This Skill allows you to search and analyze your past conversation logs, which are stored in JSONL files, enabling you to recall previous discussions or context.
~/.openclaw/agents/<agentId>/sessions/.jq to filter and extract specific information like user messages, assistant responses, costs, and tool usage.Use the session-logs skill to search all sessions for the phrase "project deadline".
High-intent search queries and answers about installing and using this skill.
To search conversation logs in JSONL format, you can filter and extract user messages, assistant responses, and cost data from session files using jq and rg for pattern matching and structural querying.
Extract specific messages from session history by applying jq filters to the JSONL files located in your agents sessions directory, targeting user messages, assistant responses, or tool usage data individually.
Yes, you need both jq and rg installed to analyze session transcripts, as jq handles JSONL data filtering and extraction while rg performs fast pattern matching within the session files.
You can retrieve cost data and tool usage from previous chat sessions by querying the JSONL session transcripts with jq, allowing you to extract and review historical context and specific metadata.
The best way to find a past decision is to search all stored session logs using rg for keyword pattern matching, then use jq to extract the relevant conversational context from the matched JSONL files.
Agent session transcripts are stored as JSONL files in the ~/.openclaw/agents/<agentId>/sessions/ directory, allowing you to perform log analysis and retrieve historical conversation context locally.
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