gitnexus-exploring

Map function calls and dependencies across Bunyan project modules.

Updated Apr 10, 2026
One-click install
npx skills add https://github.com/majedsiefalnasr/bunyan-app-cursor --skill gitnexus-exploring-majedsiefalnasr
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: gitnexus-exploring
Source: https://github.com/majedsiefalnasr/bunyan-app-cursor/tree/main/.agents/skills/gitnexus-exploring
Command: npx skills add https://github.com/majedsiefalnasr/bunyan-app-cursor --skill gitnexus-exploring-majedsiefalnasr

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify and understand the architecture and code interactions within a Bunyan project.

Core Features & Use Cases

  • Load context from gitnexus://repo/bunyan-app/context
  • Query the graph to map function calls and dependencies
  • Trace execution across components
  • Report findings on architecture and data flow

Quick Start

Load the context with gitnexus://repo/bunyan-app/context and start querying to map architecture.

Frequently Asked Questions about gitnexus-exploring

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

FAQPage Schema
How do I trace execution paths and map function calls in a Bunyan app?

Mapping codebase architecture involves querying a graph model of your project to identify component interactions and dependencies. It helps you understand how modules communicate and trace data flows within request-driven workflows.

How do I trace execution paths and map function calls in a Bunyan app?

You can trace execution paths by loading project context and querying the graph model to map function calls. This allows you to follow call chains across components and document data flows within your Bunyan application.

Can I analyze module dependencies and data flow without manual codebase inspection?

Yes, you can analyze module dependencies automatically by querying a graph-like model of your repository. This process presents a concise summary of key files and dependencies, replacing the need for manual codebase inspection.

What is the best way to document data flows across modules in request-driven workflows?

Documenting data flows across modules is best achieved by querying a graph model to trace execution across components. This approach tracks request-driven workflows and reports concise findings on architecture and data flow.

Does code exploration through graph queries work for understanding request-driven architecture?

Code exploration through graph queries works effectively for understanding request-driven architecture by mapping function calls and dependencies. It requires loading repository context to trace call chains and report data flows.

How do I start exploring my codebase architecture using graph queries?

To start exploring codebase architecture, load the project context from your repository and begin querying the graph model. This maps function calls and dependencies, allowing you to trace execution across components.