What problem does it solve? Knowledge about decisions, preferences, and project state gets scattered across chat sessions, local notes, GitHub, Linear, and databases, making it hard to find, deduplicate, and keep in sync. This Skill provides a structured workflow for classifying, storing, syncing, and retrieving knowledge across multiple storage layers. ## Core Features & Use Cases - Multi-layer storage routing: Classifies incoming knowledge and routes it to the right layer, from quick-access memory files to MCP memory graphs, GitHub/Linear, knowledge base repos, and external databases like Supabase or PostgreSQL. - Deduplication and indexing: Searches existing memory files and MCP memory before writing, updates entries instead of duplicating them, and maintains indexes and summaries. - Sync operations: Syncs conversation sessions, workspace state, and cross-source exports (Claude, ChatGPT, bookmarks, GitHub activity) into a durable knowledge base repo with sensitive data redaction. - Use Case: After a long planning session, ask to save the key decisions. The Skill checks for existing entries, writes a concise memory file, creates entities and relations in MCP memory, updates the relevant GitHub issue, and commits a session summary to the knowledge base repo. ## Quick Start Save the decisions from this session to my knowledge base and sync them with GitHub and MCP memory.