What problem does it solve? Repeated manual workflows and recurring friction across AI coding sessions often go unnoticed, so users keep re-explaining the same processes instead of turning them into reusable agent assets. ## Core Features & Use Cases - Workflow Pattern Detection: Reviews recent sessions, project notes, and existing agent assets to find repeated friction with frequency, confidence, and impact scoring. - Session Archaeology Mode: Queries the OpenCode SQLite database to analyze historical sessions across repos, caching per-session summaries and aggregating cross-repo patterns. - Smallest-Useful-Form Recommendations: Proposes prompt rules, skills, commands, custom agents, MCP permission changes, or playbooks, and asks for approval before changing any config. - Use Case: After noticing you repeatedly run the same release checks, run a reflection to get an evidence-backed proposal for a reusable command instead of re-typing the steps each time. ## Quick Start Ask the agent to run /reflect to review your recent work and suggest reusable improvements.