What problem does it solve?
This skill solves the problem of fragmented, siloed knowledge scattered across local files, project trackers, memory systems, and external data stores, eliminating the need to manually search multiple disconnected systems to find the information you need.
Core Features & Use Cases
- Multi-Layer Knowledge Routing: Automatically classify new information and store it in the optimal layer, from active project trackers (GitHub, Linear) for live engineering work to durable knowledge base repos for long-term research context.
- Automated Deduplication & Ingestion: Capture new knowledge from documents, conversations, or project updates, automatically search existing stores to avoid duplicate entries, and add only new or updated information.
- Cross-System Sync: Keep knowledge consistent across all storage layers, sync conversation history and workspace state to your knowledge base, and pull data from external sources like browser bookmarks or agent session exports into a single searchable location.
- Use Case: If you have research notes scattered across local markdown files, GitHub issues, and MCP memory, use this skill to consolidate them into a single indexed knowledge base with no duplicate entries and proper metadata tagging.
Quick Start
Use the knowledge-ops skill to ingest your latest project research notes, check for duplicates in your MCP memory and GitHub issues, and sync the finalized content to your durable knowledge base repo.
