Why is statistical analysis used instead of simple thresholds?

Statistical analysis helps distinguish between normal variance and significant performance degradation, reducing false positives in environments with variable load.

How does it detect regressions?

It uses statistical analysis and predefined thresholds to compare live metrics like response time and throughput against established baselines stored in your repository.

What is the Performance Regression Detector skill?

It is a specialized capability for Claude Code that automates the identification of performance drops in software builds by comparing current metrics to historical data.

What data does it need to work?

The skill requires access to historical performance baselines (typically located in a specific performance directory) and current metrics generated by your testing tools.

Can I use this in my CI/CD pipeline?

Yes, the skill is designed to integrate with CI/CD environments to provide automated performance validation and reporting during the build process.

Performance Regression Detector

Name: Performance Regression Detector
Author: jeremylongshore

byjeremylongshore

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1,031

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Deployment & DevOps

Identifies and analyzes performance regressions in CI/CD pipelines by comparing current metrics against historical baselines.

The Performance Regression Detector skill empowers Claude to proactively safeguard application performance by identifying degradations during the software development lifecycle. By integrating with CI/CD metrics, the skill performs statistical analysis and threshold checks on data such as response times and throughput, helping developers catch latency issues or resource bottlenecks before they reach production. It is an essential tool for teams looking to automate performance validation and ensure a consistent user experience across every build.

Key Features

01Customizable threshold violation alerts for specific metrics

021,031 GitHub stars

03Detailed regression reporting with root cause insights

04Automated baseline comparison against historical performance data

05Statistical analysis to identify significant performance shifts

06CI/CD integration for automated build validation

Use Cases

01Monitoring response time trends across multiple deployment cycles

02Validating build performance before merging code to main branches

03Analyzing throughput degradation after large-scale architectural changes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills detecting-performance-regressions

For use in Claude.ai and ChatGPT

Download Skill

Key Features

01Customizable threshold violation alerts for specific metrics

021,031 GitHub stars

03Detailed regression reporting with root cause insights

04Automated baseline comparison against historical performance data

05Statistical analysis to identify significant performance shifts

06CI/CD integration for automated build validation

Use Cases

01Monitoring response time trends across multiple deployment cycles

02Validating build performance before merging code to main branches

03Analyzing throughput degradation after large-scale architectural changes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills detecting-performance-regressions

For use in Claude.ai and ChatGPT

Download Skill