Search and analyze past conversation logs in JSONL files using jq and rg.
npx skills add https://github.com/lehalpaul/agents --skill session-logs-lehalpaul
Please help me install this Agent Skill. Skill: session-logs Source: https://github.com/lehalpaul/agents/tree/main/skills/session-logs Command: npx skills add https://github.com/lehalpaul/agents --skill session-logs-lehalpaul
This Skill allows you to search and analyze your past conversation logs, enabling you to recall information from previous interactions or understand historical context.
jq and rg to filter, extract, and summarize information from logs.Use the session-logs skill to find sessions from January 6th, 2026.
High-intent search queries and answers about installing and using this skill.
You can search past conversation logs by querying JSONL files directly to retrieve historical context and recall information from previous interactions. This allows you to audit past interactions and understand long-term conversation threads.
Yes, you need jq and rg installed and available in your system's PATH to analyze conversation history. These command-line tools are required for parsing and searching the JSONL log data.
To extract information from JSONL conversation logs, you use command-line tools like jq and rg to filter, extract, and summarize data. This approach enables direct querying of historical conversation data stored in JSONL format.
Yes, you can retrieve details from a previous chat session by querying historical conversation data stored in JSONL files. For example, you can find sessions from a specific date like January 6th, 2026, to retrieve relevant decisions.
The best way to audit past interactions in JSONL files is using command-line tools like jq and rg to search and analyze the logs. This method allows you to filter and summarize historical conversation data to understand long-term threads.
Limitations when searching large JSONL log files depend on the command-line tools jq and rg and your system's capacity to process the data. The skill is designed for retrieving historical context and auditing past interactions within these constraints.
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