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Kragen knowledge graph

Skill FridrichMethod/awesome-skills/skills/kragen-knowledge-graph

Graph-RAG SolverFrom its SKILL.md

Install
npx -y skills add FridrichMethod/awesome-skills --skill kragen-knowledge-graph

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SKILL.md

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<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA -->

KRAGEN (Knowledge Graph Enhanced RAG)

A knowledge graph-enhanced Retrieval-Augmented Generation system for biomedical problem solving, using Graph-of-Thoughts (GoT) reasoning.

When to Use

  • Complex Reasoning: Questions requiring multi-hop deduction (e.g., "How does gene A influence disease B via protein C?").
  • Hypothesis Verification: Checking if a proposed mechanism is supported by existing knowledge graphs.
  • Literature Synthesis: Combining facts from structured DBs and unstructured text.

Core Capabilities

  1. Graph Retrieval: Query biomedical knowledge graphs (e.g., PrimeKG, SPOKE).
  2. Graph-of-Thoughts: structured reasoning over retrieved nodes.
  3. Vector DB Integration: Combines graph data with vector embeddings for hybrid search.

Workflow

  1. Input: Natural language question.
  2. Retrieval: Fetch relevant sub-graph and similar text chunks.
  3. Reasoning: LLM traverses the graph to find connecting paths.
  4. Answer: Generate response with citation of graph nodes.

Example Usage

User: "Explain the mechanism connecting BRCA1 mutations to ovarian cancer."

Agent Action:

python -m kragen.solve --question "BRCA1 mutations to ovarian cancer mechanism"
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it

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