What problem does it solve? AI coding sessions lose hard-won project knowledge between conversations, forcing developers to re-explain patterns, pitfalls, and past decisions every time. This Skill persists that knowledge in a unified graph so it can be searched and recalled on demand. ## Core Features & Use Cases - Unified Knowledge Search: Query across tasks, SOPs, system docs, and memories with one command, returning only relevant context (~1-2k tokens). - Memory Capture: Store patterns, pitfalls, decisions, and learnings with confidence scores, concept tags, and optional TRIZ contradiction annotations. - Graph Maintenance: Run health checks, reconcile disk files against graph nodes, repair dangling edges, prune low-confidence memories, and resolve superseded knowledge. - Use Case: Before modifying authentication code, ask "what do we know about auth?" to surface the pitfall that auth changes break session tests, plus the decision record explaining why JWT was chosen over sessions. ## Quick Start Ask the assistant to initialize the knowledge graph and then show everything the project knows about authentication.