reflect

Capturing learnings from conversations involves analyzing sessions to extract corrections, preferences, patterns, edge cases, and anti-patterns. This skill automates that analysis and saves findings to Forgetful Memory, creating a feedback loop that improves future team interactions.

Session reflection is the process of analyzing discussions to identify corrections, preferences, patterns, edge cases, and anti-patterns. It synthesizes these extracted learnings into actionable guidance, tagging and linking them to specific skills or projects for traceability.

Yes, Forgetful Memory integration is required. This skill relies on Forgetful Memory to save and organize extracted corrections, preferences, and patterns, ensuring learnings persist across sessions and apply to future interactions.

Yes, you can link captured learnings to specific skills, projects, and entities. This ensures full traceability, allowing teams to track how extracted patterns, edge cases, and anti-patterns map directly to relevant workflows and skill improvements.

To graduate learnings into a skill, run a reflection session to analyze the current conversation and capture findings, then use the synthesize command targeting the specific skill. This converts extracted patterns and corrections into actionable workflow improvements.

Yes, the analysis applies across sessions and skills. It automatically analyzes discussions to extract corrections and preferences, ensuring that learnings captured from one interaction are synthesized into improvements applicable to future skills and workflows.