codebase-memory-quality

Name: codebase-memory-quality
Availability: InStock
Author: gganbukim

Identify dead code and complexity hotspots via graph-based analysis.

Updated May 4, 2026

Search Tags:#code quality #static analysis #complexity analysis #dead code #dependency graph #refactor candidates #cleanup opportunities

Ready to run

npx skills add https://github.com/gganbukim1/myskills --skill codebase-memory-quality-gganbukim1

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: codebase-memory-quality
Source: https://github.com/gganbukim1/myskills/tree/main/codebase-memory-quality
Command: npx skills add https://github.com/gganbukim1/myskills --skill codebase-memory-quality-gganbukim1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Codebases often accumulate dead code, unused functions, and high-complexity areas that slow development and increase bugs.

Core Features & Use Cases

Dead Code Detection: Identifies unreferenced functions using codebase-memory-mcp graph search.
Complexity Analysis: Surfaces high fan-out functions and the most-connected hotspots that may need refactoring.
Cleanup Scenarios: Use it when planning refactors, addressing cleanup opportunities, or reviewing changes for risk.

Quick Start

Use the codebase-memory-quality skill to locate dead code and high-complexity functions in your repository without manually searching files.

Frequently Asked Questions about codebase-memory-quality

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

FAQPage Schema

How do I find dead code and unreferenced functions in my codebase?▼

Dead code and unreferenced functions are identified by running codebase-memory-mcp graph search with degree filters, eliminating the need to manually search files for unused functions.

What is the best way to detect complexity hotspots for refactoring?▼

Complexity hotspots are detected by analyzing high fan-out functions and high-degree call relationships in the codebase graph, surfacing the most connected functions that need refactoring.

How do I discover cleanup opportunities before planning a refactor?▼

Cleanup opportunities are discovered by applying graph-based analysis to locate unreferenced functions and complexity hotspots, providing a clear list of dead code and high-risk areas for maintenance reviews.

Do I need codebase-memory-mcp to run static analysis for dead code?▼

Yes, graph-based static analysis requires invoking codebase-memory-mcp search_graph with degree filters to identify unreferenced functions and high fan-out relationships before any manual file searching.

Can I use dependency graph analysis for maintenance reviews?▼

Dependency graph analysis applies directly to maintenance reviews by surfacing unused functions and high-degree call relationships that increase bug risk and slow development.

What are the limitations of graph-based dead code detection?▼

Graph-based detection focuses on unreferenced functions and high fan-out call relationships, meaning it identifies structural dead code but does not assess runtime behavior or dynamically loaded code.