What problem does it solve? Operating a gbrain knowledge base involves many moving parts — content sync, vector embeddings, nightly dream cycles, MCP server connectivity, and database engines (PGLite or Postgres/Supabase) — and failures like stale locks, WASM crashes, or quota errors can silently break the whole system. ## Core Features & Use Cases - Full CLI lifecycle reference: Covers gbrain sync, embed, doctor, dream, mcp, brainstorm, capture, and publish with flags, best practices, and cron scheduling patterns. - Deep troubleshooting playbooks: Step-by-step recovery for PGLite lock contention, WASM runtime crashes after WSL2 kernel upgrades, Supabase auto-pause, embedding 429 rate limits, and autopilot PATH failures. - Automation patterns: Python wrapper for running gbrain from scripts, cron job templates for 15-minute syncs and nightly dream cycles, and background execution for multi-hour bulk imports. - Use Case: Your nightly dream cycle starts failing with PATTERNS_PHASE_FAIL after a config change. Use the dream-cycle troubleshooting reference to identify the missing provider prefix in the model string and fix it with gbrain config set. ## Quick Start Ask the agent to run a gbrain health check with doctor and fix any stale locks or sync issues it finds.