logging-session

You can automatically save AI coding session logs by integrating a Stop hook that triggers when a session ends, capturing the user query, thought process, final result, and file paths into a structured schema for later recall.

Querying AI session logs by project and date range is done through flexible query formats that filter records by project name, date, or session ID, outputting results as Markdown, AI-friendly text, or JSON.

Yes, you can export AI session logs directly into an Obsidian vault for seamless knowledge capture, transferring structured session records and weekly project summaries into your notes.

Generating weekly project summaries from AI conversation logs involves grouping stored records by project name, creating category breakdowns and detailing per-session outcomes to support reporting.

The session logging tool uses SQLite to store structured records of AI coding sessions, capturing queries, solutions, outcomes, and file paths to enable fast recall and flexible querying.

Linking related AI sessions to build conversation threads requires using thread support features to connect separate session records, preserving the context of questions and solutions across project work.