graphify-flow

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Install and use graphify from Hermes to build knowledge graphs for codebases, docs, papers, or mixed folders, then inspect GRAPH_REPORT.md and graph outputs.

Undermybelt By Undermybelt schedule Updated 6/7/2026

name: graphify-flow description: Install and use graphify from Hermes to build knowledge graphs for codebases, docs, papers, or mixed folders, then inspect GRAPH_REPORT.md and graph outputs.

Graphify Workflow

Use this skill when the user wants structural understanding of a repo or folder.

Prerequisites:

  • graphify CLI available on PATH
  • Python package graphifyy installed

Quick checks:

  • graphify --help
  • python3 -c "import graphify"

Typical workflow:

  1. Choose a target folder.
  2. Run graphify on it:
    • graphify install --platform codex installs always-on instructions for Codex-style agents.
    • For graph generation itself, use the installed skill command in the target agent environment or run graphify-enabled workflows in the project.
  3. Inspect outputs in graphify-out/:
    • GRAPH_REPORT.md
    • graph.json
    • graph.html
  4. Summarize god nodes, communities, surprising connections, and suggested questions.

Recommended commands:

  • graphify --help
  • graphify codex install
  • graphify claude install
  • graphify hook install

Notes:

  • graphify is strongest for mixed corpora and unfamiliar codebases.
  • It is useful as a structure-first orientation layer before raw grep/search.
  • Keep output review focused on architecture, rationale, and cross-file relationships.

Important local finding:

  • The packaged graphify CLI from graphifyy may expose only install/hook/benchmark commands, not a direct graph-build command.
  • For one-shot local code-only graph generation, use the internal rebuild entrypoint instead: python3 -c "from graphify.watch import _rebuild_code; from pathlib import Path; _rebuild_code(Path('/path/to/project'))"
  • This writes into /path/to/project/graphify-out/ and at minimum produces GRAPH_REPORT.md and graph.json.

Compatibility pitfall discovered:

  • On some environments, graphifyy 0.3.1 can fail during JSON export because networkx.readwrite.json_graph.node_link_data may expect link= instead of edges=.
  • If export fails with node_link_data() got an unexpected keyword argument 'edges', patch graphify/export.py so to_json() tries edges="links" first and falls back to link="links" on TypeError.

Environment mismatch pitfall:

  • Do not assume python3 -c "from graphify.watch import _rebuild_code ..." works in the user's interactive shell just because it works in Hermes.
  • Hermes may have a different Python environment/site-packages than the user's terminal.
  • Before giving a Python import-based rebuild command, first verify in the user's shell context with: python3 -c "import graphify, sys; print(sys.executable); print(graphify.__file__)"
  • If the user's shell reports ModuleNotFoundError: No module named 'graphify', stop suggesting Python import rebuild commands.

Method correction rule:

  • Prefer the actual installed CLI/help output over assumptions from prior environments.
  • Ask the user to run graphify or graphify --help first, then tailor instructions to the subcommands that really exist.
  • If the local graphify binary exposes only installer/hook commands and no build/rebuild command, conclude that graph generation is not available from that installation and do not keep retrying fake rebuild invocations.
  • In that case, explicitly tell the user the repo-local graphify rebuild rule is currently non-executable in their environment and continue the main task without blocking on graphify, unless they provide the real generator command/script.
Install via CLI
npx skills add https://github.com/Undermybelt/hermes-skills --skill graphify-flow
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