bayuh85

Graphloom — Data skill for Claude Code

Data community

Turn your repo into a queryable knowledge graph for coding agents: offline code/SQL/docs graph, path + explain with file:line evidence, MCP server, LLM ask.

How to install Graphloom

This entry records only its repository, not the path inside it, so there is no exact command to give. Open bayuh85/graphloom and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Graphloom does

Turn your repo into a queryable knowledge graph for coding agents: offline code/SQL/docs graph, path + explain with file:line evidence, MCP server, LLM ask. Runs on AtmoRouter, a cheap AI API gateway and OpenRouter alternative: atmorouter.dev

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README

Graphloom

Coding agents answer architecture questions by grepping and reading file after file. They burn tokens and still miss how the repository fits together: which module calls which function, which doc names which symbol, which handler touches which table. Graphloom weaves that map once, offline, and lets an agent ask a short question against it.

What it does

`graphloom build` walks a repository and writes three files under `.graphloom/`:

File Role
graph.json Versioned graph (graphloom.graph/v1). Every edge has a provenance tag and a file:line excerpt.
REPORT.md Hubs, isolated modules, cross-layer links, unread config keys, and questions the graph can already answer.
graph.html One self-contained viewer. Search, filter, click a node. No CDN, no network.

You then query that file instead of the tree:

The offline build understands:

  • Python via the stdlib ast module: modules, classes, functions, imports, and calls
  • JavaScript / TypeScript with a small scanner: imports, exported functions and classes, calls, fetch URLs
  • SQL CREATE TABLE nodes, plus foreign keys
  • Markdown headings, with edges to symbols written in backticks
  • TOML / YAML / JSON keys, with edges from code that reads them

An optional `--semantic` pass sends documentation chunks, not source code, to a model and grounds the concepts it returns onto nodes that already exist.

Quickstart

pip install -e .
cd examples/harbor-shop
graphloom build .
graphloom query invoices
graphloom path post_invoice se