One-click install
npx skills add https://github.com/ayehiaa/my-travel-assistant --skill diagramming-code
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: diagramming-code
Source: https://github.com/ayehiaa/my-travel-assistant/tree/main/.agents/skills/diagramming-code
Command: npx skills add https://github.com/ayehiaa/my-travel-assistant --skill diagramming-code

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires trailmark, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you visualize complex code architecture by converting a code graph into clear Mermaid diagrams that communicate relationships, structure, and risk-relevant data flows.

Core Features & Use Cases

  • Generates Mermaid diagrams from Trailmark code graphs covering call graphs, class hierarchies, module dependency maps, containment structure, complexity heatmaps, and data-flow/attack-surface visualizations.
  • Guided diagram selection by intent so the requested view maps to an appropriate diagram type and parameters like focus and depth.
  • Accuracy-first approach that relies on Trailmark’s parsed graph instead of hand-crafted Mermaid from raw source inspection.

Quick Start

Ask the assistant to run the diagramming script on your target directory to generate a Mermaid call graph focused on your entry function, wrapped for rendering as a Mermaid diagram.

Frequently Asked Questions about diagramming-code

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a Mermaid diagram from a code graph?

You can generate Mermaid diagrams by running the diagram.py wrapper with a valid --type parameter, relying on Trailmark's parsed code graph to produce call graphs, class hierarchies, and module dependency maps.

What types of architecture diagrams can I create from code visualization?

Code visualization supports generating Mermaid call graphs, class hierarchies, module dependency maps, containment diagrams, complexity heatmaps, and entrypoint-to-sensitive-function data-flow visualizations.

Do I need Trailmark to produce call graphs and module dependency maps?

Yes, you need Trailmark because the Skill depends on its code graph preanalysis for data-flow enrichment, relying on the parsed graph to ensure accuracy instead of hand-crafting Mermaid from raw source inspection.

Can I focus on a specific function or module when generating a data-flow analysis diagram?

Yes, you can use the optional --focus and traversal parameters with the diagram.py wrapper to target specific entry functions and control the depth of your data-flow analysis visualization.

What is the best way to visualize entrypoint-to-sensitive-function data flows in a codebase?

The best way is using the data-flow diagram type, which relies on Trailmark's preanalysis to map and render attack-surface flows from entrypoints to sensitive functions in Mermaid format.

Why should I use a parsed code graph instead of hand-crafting Mermaid diagrams from source code?

Using a parsed code graph ensures an accuracy-first approach by relying on Trailmark's structural analysis, preventing human error and omissions that occur when manually inspecting raw source code to build architecture diagrams.