Log chat messages to a local SQLite database with timestamps and session IDs.
npx skills add https://github.com/besoeasy/open-skills --skill chat-logger
Please help me install this Agent Skill. Skill: chat-logger Source: https://github.com/besoeasy/open-skills/tree/main/skills/chat-logger Command: npx skills add https://github.com/besoeasy/open-skills --skill chat-logger
This Skill provides a robust solution for logging all chat messages to a local SQLite database, enabling searchable history, auditing, and analytics without relying on external services.
Log a user message with the content "Hello, how are you?" to session "session_123".
High-intent search queries and answers about installing and using this skill.
To log chat messages to SQLite, use a defined schema capturing session IDs, timestamps, sender, content, and metadata. This approach stores interactions locally, enabling searchable history and auditing without external services.
Yes, you can store conversation history locally for auditing by logging every chat interaction to a SQLite database. This allows agents to review past customer conversations and search for common solutions.
Yes, this chat logging approach supports both Python and Node.js implementations. It uses a defined database schema for messages and metadata, allowing you to integrate it into either environment seamlessly.
You can search past chat logs by querying the local SQLite database using keywords or session IDs. This enables efficient retrieval of specific conversation history and content from the searchable archive.
The best way to audit chat interactions without external services is logging them to a local SQLite database. This provides a reliable, persistent record for reviewing interactions and understanding conversation patterns.
When logging chat messages to SQLite, the captured metadata includes timestamps, session IDs, sender information, message content, and additional metadata. This schema enables efficient querying and auditing of conversation history.
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