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Dependency Graph

Community
athola
dependency-graph

Generates a Mermaid dependency graph showing import relationships between modules. Use when analyzing coupling, finding circular deps, or planning refactors.

Overview

Publisherathola
Repositoryclaude-night-market
Skill namedependency-graph
Stars
343
Forks
37
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by athola on GitHub. Read the source before you install it.

Installation

Install the Dependency Graph AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/athola/claude-night-market/tree/master/plugins/cartograph/skills/dependency-graph
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/athola/claude-night-market.git /tmp/claude-night-market
mkdir -p .claude/skills
cp -r /tmp/claude-night-market/plugins/cartograph/skills/dependency-graph .claude/skills/dependency-graph
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dependency Graph in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dependency Graph on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dependency Graph is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Dependency Graph

Generate a Mermaid flowchart showing import and dependency relationships between modules, packages, or plugins.

When To Use

  • Understanding what depends on what
  • Finding circular dependencies
  • Analyzing coupling between modules
  • Planning refactoring by seeing dependency impact
  • Answering "what breaks if I change this?"

When NOT To Use

  • Runtime call paths (use cartograph:call-chain)
  • Type hierarchies (use cartograph:class-diagram)

Workflow

Step 1: Explore the Codebase

Dispatch the codebase explorer agent:

Agent(cartograph:codebase-explorer)
Prompt: Explore [scope] and return a structural model.
Focus on import statements and cross-module dependencies
for a dependency graph. Track both internal and external
imports.

Step 2: Generate Mermaid Syntax

Transform the structural model into a Mermaid flowchart with directed edges representing dependencies.

Rules for dependency graphs:

  • Use flowchart LR (left-right) for dependency direction
  • Each node is a module or package
  • Edges point from dependent to dependency (A --> B means "A depends on B")
  • Color-code by dependency type:
    • Default arrows for internal dependencies
    • Dotted arrows (-.->) for external/optional deps
    • Thick arrows (==>) for critical path dependencies
  • Group into subgraphs by package/plugin
  • If depth parameter given, limit transitive dependencies
  • Highlight circular dependencies with red styling

Example output:

Step 3: Render via MCP

Call the Mermaid Chart MCP to render:

mcp__claude_ai_Mermaid_Chart__validate_and_render_mermaid_diagram
  prompt: "Dependency graph of [scope]"
  mermaidCode: [generated syntax]
  diagramType: "flowchart"
  clientName: "claude-code"

If rendering fails, fix syntax and retry (max 2 retries).

Step 4: Present Results

Show the rendered diagram with analysis notes:

  • Total modules and dependency count
  • Most-depended-on modules (high fan-in)
  • Modules with most dependencies (high fan-out)
  • Circular dependencies if any detected

Exit Criteria

  • Mermaid flowchart LR syntax generated with directed edges from dependent to dependency (A --> B means "A depends on B")
  • mcp__claude_ai_Mermaid_Chart__validate_and_render_mermaid_diagram called and returns without error
  • Analysis notes include total module count, highest fan-in modules, and highest fan-out modules
  • Circular dependencies, if detected, are highlighted with red styling and listed explicitly in the analysis notes
  • External dependencies use dotted arrows (-.->) distinct from internal dependency arrows

Frequently asked questions

What does the Dependency Graph AI skill do?

Generates a Mermaid dependency graph showing import relationships between modules. Use when analyzing coupling, finding circular deps, or planning refactors.

Why use Dependency Graph on TypingMind?

Because you install it once and use it with any model. Dependency Graph is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dependency Graph in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/athola/claude-night-market/tree/master/plugins/cartograph/skills/dependency-graph. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dependency Graph?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dependency Graph?

As many as you like. As long as a model supports skills, you can use Dependency Graph with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dependency Graph AI skill free?

Yes. It is published on GitHub by athola under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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