What dimensions does this skill evaluate?

It assesses five key dimensions: Consistency, Intuitivity, Describability, Agility, and Density to provide a holistic view of code quality.

Is this skill meant for automated reporting?

Yes, it generates structured markdown reports that are ideal for inclusion in Pull Request comments or documentation.

How does it define code 'Density'?

Density evaluates the expressiveness of the software; it rewards code that packs high conceptual value into minimal structure without redundant abstractions.

Does it penalize mid-development changes?

No, the framework values iteration over perfection, only penalizing 'oscillation' (indecisive back-and-forth) rather than 'convergence' toward a better solution.

Does it provide quantitative data?

Yes, it includes a calculation script that returns metrics like commit count, duration in hours/days, and velocity in a JSON format.

Performance & Decision Analyzer

Name: Performance & Decision Analyzer
Author: qmu

byqmu

0•

生产力与工作流

Evaluates development branch quality and decision-making logic across five qualitative dimensions and quantitative metrics.

Analyze-Performance is a comprehensive evaluation framework designed to audit the quality of development branches and the decision-making process behind them. It bridges the gap between raw data and architectural insight by combining automated quantitative metrics—such as commit velocity and development duration—with a structured qualitative assessment of consistency, intuitivity, and code density. This skill is particularly valuable during code reviews and project retrospectives, as it helps teams move beyond simple syntax checking to understand the logical maturity and iterative efficiency of their development cycles.

主要功能

01Evidence-based analysis of code density and architectural agility

02Automated branch velocity and commit frequency calculation

030 GitHub stars

04Standardized markdown reports for peer code reviews

05Quantitative metrics export in structured JSON format

06Five-dimensional qualitative decision-making framework

使用场景

01Monitoring development velocity and iteration efficiency on complex feature branches

02Post-sprint retrospectives to assess developer decision-making patterns

03Automating qualitative feedback during peer code reviews

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add qmu/workaholic analyze-performance

For use in Claude.ai and ChatGPT

Download Skill