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 work, project notes, and existing agent assets to find repeated friction and recommend the smallest useful improvement. - Session Archaeology Mode: With --sessions, queries the OpenCode SQLite database to analyze historical sessions across repos, aggregating frictions, models, agents, and tools used. - Evidence-Driven Proposals: Scores candidates by frequency, cost, risk, stability, and coverage, then proposes changes before writing anything. - Use Case: After noticing you repeatedly run the same test-fix loop, run /reflect --sessions --last 100 to get a ranked report of recurring patterns and a proposal to add a /test-ci command. ## Quick Start Ask the agent to run /reflect on your recent sessions and suggest which repeated workflows should become reusable skills or commands.