What problem does it solve? Repeated manual workflows and recurring friction across AI coding sessions go unnoticed, so teams keep re-explaining the same processes instead of turning them into reusable skills, commands, or agent configurations. ## 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: Queries the OpenCode SQLite database directly to analyze historical sessions across repos, with per-session summaries cached as JSON for token-efficient aggregation. - Smallest-Useful-Form Recommendations: Proposes the least powerful fix (prompt rule, skill, command, agent, MCP permission, or playbook) and asks for approval before changing any config. - Use Case: After noticing you repeatedly run the same release checks, run /reflect release workflow 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 on your recent sessions to find repeated workflows worth turning into reusable skills or commands.