Can this skill analyze other Claude Code skills?

Yes, it includes a dedicated Skill Analysis operation that assesses the build time, efficiency gains, and structural excellence of your skill ecosystem.

What types of code metrics does the Analysis skill collect?

It analyzes cyclomatic complexity, lines of code (LOC), function/class counts, duplication levels, and comment density to provide a holistic quality score.

What are the typical outputs of an analysis operation?

Each operation generates a detailed report containing metrics, identified patterns or 'smells', a quality assessment, and a prioritized list of actionable recommendations.

How does it help with process optimization?

By mapping workflow steps and measuring active versus wait time, it identifies specific bottlenecks and rework cycles to suggest parallelization or automation opportunities.

Systematic Analysis & Insights

Name: Systematic Analysis & Insights
Author: adaptationio

byadaptationio

Analytics & Monitoring

Performs comprehensive analysis of code quality, development workflows, and skill effectiveness to generate actionable insights.

About

The Analysis skill provides a structured framework for evaluating technical ecosystems through five specialized operations: Code, Skill, Process, Data, and Pattern Recognition. It helps developers transform raw project information into data-driven decisions by identifying technical debt, uncovering workflow bottlenecks, and assessing the effectiveness of custom AI skills. This skill is essential for teams looking to maintain high code standards and optimize their development lifecycle through objective metrics and recurring pattern discovery.

Key Features

Statistical trend identification and data-driven insights
Systemic pattern recognition across diverse project artifacts
0 GitHub stars
Workflow bottleneck identification and cycle-time analysis
Skill ecosystem effectiveness and usage tracking
Multi-dimensional code quality and complexity assessment

Use Cases

Auditing large codebases to prioritize refactoring and technical debt reduction
Optimizing development processes by identifying inefficiencies and automation opportunities
Evaluating and refining the performance of custom Claude Code skill libraries

About

Key Features

Statistical trend identification and data-driven insights
Systemic pattern recognition across diverse project artifacts
0 GitHub stars
Workflow bottleneck identification and cycle-time analysis
Skill ecosystem effectiveness and usage tracking
Multi-dimensional code quality and complexity assessment

Use Cases

Auditing large codebases to prioritize refactoring and technical debt reduction
Optimizing development processes by identifying inefficiencies and automation opportunities
Evaluating and refining the performance of custom Claude Code skill libraries