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graphify macos setup
Install, integrate, and operate Graphify knowledge graphs for AI coding agents on macOS.
$9
graphify macos setup
Example session with this skill installed
I need to set up Graphify for my project in ~/work/inventory-service so my AI agent understands the architecture. Fix any PATH issues if they come up.
- Read your context and instructions
- Compiled the graphify macos setup
- Generated the document
I have successfully bootstrapped Graphify and integrated it with your project. The installation used uv to ensure an isolated environment, and I have staged the Claude Code integration hook to avoid self-modification permission errors.
Graphify Setup Summary
| Component | Status | Detail |
|---|---|---|
| Tooling | Installed | graphifyy (v1.2.0) via uv |
| Environment | Verified | Python 3.12.4, PATH updated |
| Integration | Staged | Claude PreToolUse hook ready |
| Project | ~/work/inventory-service | Initialized for graph generation |
Staged Claude Configuration
Since I cannot modify my own active settings directly, I have generated a merged configuration file. Run this command to activate the Graphify integration:
cp .claude/settings_graphify_staged.json .claude/settings.json
Next steps
- Run the
cpcommand above to enable the/graphifycommand and automated report reading. - Start a fresh Claude Code session and run
/graphify .to build your first knowledge graph. - Run
graphify hook installif you want the graph to update automatically on every git commit.
graphify-macos-setup.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
Developers spend too much time manually grepping repositories to understand architectural relationships. Standard RAG tools often miss the structural context between files, leading to incomplete or incorrect answers from coding assistants.
What it does
- Automates the installation of Graphify via
uvorpipxon macOS with PATH verification. - Injects architectural awareness into Claude Code using the
PreToolUsehook and/graphifycommand. - Generates interactive knowledge graphs (HTML), machine-readable JSON, and
GRAPH_REPORT.mdfor agent consumption. - Configures git hooks to keep the codebase graph updated automatically on every commit or branch switch.
- Executes complex structural queries like shortest-path analysis between components and plain-language relationship explanations.
Frameworks & tools
macOS 13+, zsh, Python 3.10+, Homebrew, uv, Claude Code, and tree-sitter.
Why this beats prompting it yourself
Standard prompts cannot fix environment PATH issues, handle the non-obvious graphifyy PyPI naming collision, or safely modify .claude/settings.json without triggering self-modification blocks. This skill includes pre-built bootstrap scripts that handle idempotent setup and complex shell integrations that a generic LLM would likely hallucinate or fail to execute.
Use cases
- Onboarding to a large, undocumented codebase by visualizing component hierarchies.
- Tracing data flow from an API endpoint to a database handler using shortest-path queries.
- Ensuring AI agents have high-level architectural context before they start writing code.
- Maintaining a live map of project dependencies that updates during the development cycle.
Known limitations
Interactive visualizations in graph.html may not render correctly in Safari due to canvas issues; Chrome or Chromium is required. Build times for projects exceeding 400 files can take over 10 minutes due to semantic processing.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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