Distill unstructured documentation and code into a queryable knowledge graph via MCP tool calls.
npx skills add https://github.com/phanijapps/engram --skill engram-distill
Please help me install this Agent Skill. Skill: engram-distill Source: https://github.com/phanijapps/engram/tree/main/.claude/skills/engram-distill Command: npx skills add https://github.com/phanijapps/engram --skill engram-distill
This skill solves the problem of fragmented, disposable AI context by enabling the creation of a persistent, source-grounded knowledge graph that links conceptual understanding directly to code and documentation.
Use the engram-distill skill to scan the current repository and bridge the authentication concepts found in the documentation to the corresponding middleware code.
High-intent search queries and answers about installing and using this skill.
To build a queryable knowledge graph from unstructured documentation and code, distill the source materials into entities and relationships using deterministic MCP tool calls. This process organizes information into technical, documentation, and conceptual layers for reliable recall.
To connect high-level domain concepts to specific code symbols, use semantic bridging within a project-scoped workspace. This links domain understanding directly to technical artifacts and documentation, preventing orphan knowledge and ensuring agents grasp business logic.
Yes, you need a configured engram-mcp server to persist agentic memory and maintain idempotency across extraction batches. The server manages the knowledge graph storage and ensures semantic bridges remain auditable during codebase understanding.
The best way to structure durable agentic memory is to organize extracted knowledge into multi-layer graphs separating technical, documentation, and conceptual data. This structured approach ensures persistent, source-grounded recall across long-running AI project sessions.
AI agents lose context about business logic because standard sessions use disposable memory. By distilling RFCs and design notes into a persistent knowledge graph, the agent maintains a structured, auditable link between conceptual domain logic and implementation artifacts.
Yes, you can manage knowledge graph entities and relationships within a project-scoped workspace. The workspace isolates extraction batches and semantic bridges, ensuring deterministic MCP tool calls maintain data integrity and idempotency for the specific project.
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