graph-research

Generate codebase research reports using Graphify and Beads.

2|1|Updated Apr 7, 2026

Search Tags:#code review #task management #dependency analysis #code research #graph analysis

Ready to run

npx skills add https://github.com/bigeasyfreeman/adlc --skill graph-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: graph-research
Source: https://github.com/bigeasyfreeman/adlc/tree/main/skills/graph-research
Command: npx skills add https://github.com/bigeasyfreeman/adlc --skill graph-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires graphify, beads, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill enhances ADLC's research capabilities by leveraging graph-backed insights and task memory, providing a comprehensive understanding of the codebase and aiding in efficient task management.

Core Features & Use Cases

Graph-Backed Research: Utilizes Graphify for codebase topology, compatibility, and reuse discovery.
Task Memory: Employs Beads for dependency-aware decomposition, ready-work selection, and durable agent memory.
Use Case: When preparing for a code review, this Skill can help identify related modules, potential compatibility issues, and dark-code hotspots, streamlining the review process.

Quick Start

Run the graph-research skill to generate a comprehensive research report for the current codebase.

Frequently Asked Questions about graph-research

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

FAQPage Schema

How do I identify code compatibility issues and dark-code hotspots before a code review?▼

Code review preparation requires identifying related modules and dark-code hotspots. Graph-backed research analyzes codebase topology to discover compatibility issues and reuse opportunities, streamlining the review process.

How does graph analysis work for codebase topology and dependency discovery?▼

Graph analysis for codebases works by mapping topology and dependencies to provide structural insights. It utilizes graph frameworks to discover code reuse patterns and identify compatibility bottlenecks across modules.

What is dependency-aware task decomposition in software development workflows?▼

Dependency-aware task decomposition is breaking down work based on code structure relationships. It employs task memory to track dependencies, enabling ready-work selection and efficient task execution in development workflows.

Do I need Graphify and Beads to run codebase analysis and task management?▼

Yes, you need Graphify and Beads to run codebase analysis and task management. Graphify provides graph-backed topology insights, while Beads handles dependency-aware decomposition and durable agent memory.

Can I use task memory for durable agent state during code research?▼

Task memory can be used for durable agent state during code research. It tracks dependency-aware decomposition and ready-work selection, maintaining context across complex software development workflows.

What is the best way to generate a comprehensive research report for my current codebase?▼

The best way to generate a comprehensive research report is integrating graph-backed insights with task memory. This approach analyzes codebase topology and manages dependencies to produce in-depth code understanding.