What problem does it solve? Repeated manual workflows and recurring friction across AI coding sessions go unnoticed, so users keep re-explaining the same processes instead of turning them into reusable skills, agents, commands, or configuration. ## Core Features & Use Cases - Workflow Pattern Detection: Reviews recent sessions, project notes, and existing agent assets to find repeated friction with frequency, cost, and confidence scoring. - Session Archaeology Mode: With --sessions, 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 the least powerful fix (prompt rule, skill, command, agent, playbook, or no change) and asks for approval before editing any files. - Use Case: After noticing you repeatedly run the same release checklist, run /reflect release workflow to get an evidence-backed proposal for a reusable command or playbook. ## Quick Start Ask the agent to run /reflect on your recent work to identify repeated workflows worth turning into reusable assets.