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Exposes graph-based retrieval as a tool capability via `query_graph`. Reads normalized graph store files, builds a query-relevant subgraph, and returns LLM-friendly semantic triples with replayable evidence metadata.

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$ npx -y skills add study8677/repobrain --skill graph-retrieval --agent claude-code

SKILL.md

graph-retrieval.SKILL.md
name: graph-retrieval
description: Exposes graph-based retrieval as a tool capability via `query_graph`. Reads normalized graph store files, builds a query-relevant subgraph, and returns LLM-friendly semantic triples with replayable evidence metadata.

Graph Retrieval Skill

Purpose

Expose graph-based retrieval as a tool capability without breaking the existing RepoBrain execution chain.

Tool

  • `query_graph(query, max_hops=2, workspace='.')`

Behavior

  • Reads normalized graph store files under `.repobrain/graph/`.
  • Builds a query-relevant subgraph.
  • Returns LLM-friendly semantic triples plus replayable evidence metadata.

Output Contract

{
  "summary": "...",
  "triples": [["subject", "predicate", "object"]],
  "evidence": [{"retrieval_id": "...", "tool_name": "..."}],
  "nodes": [...],
  "edges": [...]
}

Design Notes

  • Keeps tool-driven and replayable architecture.
  • Does not bypass pipeline.
  • Intended for structure/dependency questions and context enrichment.
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Questions about graph-retrieval.

Which coding agents can use graph-retrieval?
graph-retrieval installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.