概要
Session Learning is a specialized capability for the Claude Code environment that transforms transient session data into persistent, actionable knowledge. By analyzing session transcripts at termination, the skill extracts error patterns, workflow improvements, and architectural decisions into structured YAML files. When a new session begins, it uses a lightweight keyword-matching algorithm to surface and inject relevant historical context, ensuring the AI avoids repeating past mistakes and leverages previously discovered shortcuts without the need for manual documentation overhead.