research

Trace execution paths and document data flows across code components.

Updated Jan 22, 2026
One-click install
npx skills add https://github.com/Hoang604/get-thing-done --skill research-hoang604
Or copy as Structured Prompt for Agent
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Skill: research
Source: https://github.com/Hoang604/get-thing-done/tree/main/skills/research
Command: npx skills add https://github.com/Hoang604/get-thing-done --skill research-hoang604

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Trace and document how code actually behaves to improve debugging, onboarding, and auditability.

Core Features & Use Cases

  • Explicitly trace data origins, transformations, and destinations.
  • Map dependencies and interactions across components.
  • Use in code reviews, feature investigations, and orphan-event audits.

Quick Start

Provide a concise trace of a function's execution path and document how data flows between components.

Frequently Asked Questions about research

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

FAQPage Schema
How do I trace code execution paths and document how a function actually behaves?

To trace code execution paths, you map explicit data lineage, dependencies, inputs, and outputs. This documents actual code behavior across components, supporting reliable debugging and auditability without relying on speculative conclusions.

What is data lineage and how does it help with debugging complex codebases?

Data lineage tracks data origins, transformations, and destinations. For debugging, it clarifies flows and component relationships across varying codebase sizes, ensuring you understand exact execution paths rather than guessing at error modes.

Can I use this to map dependencies and interactions for a code review or feature investigation?

Yes, you can map dependencies and interactions across components for code reviews and feature investigations. It explicitly traces data flows and potential error modes, which also supports orphan-event audits and governance.

Does this approach work for codebases of varying sizes or only large enterprise applications?

Tracing code behavior works for codebases of varying sizes. It is applicable anywhere understanding data origins, flows, and component relationships is essential for debugging, onboarding, and auditability.

How do I avoid speculative conclusions when auditing code behavior and data flows?

To avoid speculative conclusions during code audits, enforce explicit documentation of data lineage, dependencies, inputs, outputs, and potential error modes. This ensures all traced execution paths reflect actual behavior.

What's the best way to document code behavior for onboarding and auditability?

The best way to document code behavior for onboarding is providing a concise trace of a function's execution path. Explicitly map data flows between components to ensure reliable auditability and governance.