What metrics are supported?

The skill supports common performance indicators such as response latency, requests per second (throughput), and error rates, provided they are accessible via the CI environment.

How does this skill detect regressions?

It compares current build metrics against stored historical baselines using statistical analysis and predefined thresholds to identify significant performance drops.

Where should I store my baseline data?

Baselines should be stored in the performance/baselines directory within your project's base directory for the skill to access them.

Can I use this for production monitoring?

While optimized for CI/CD pipelines, it can analyze any set of performance metrics provided they are formatted correctly and have a corresponding baseline.

Does it offer root cause analysis?

Yes, the generated report includes a summary of regressed metrics and recommendations for investigation to help developers pinpoint the cause of the degradation.

Performance Regression Detector

Name: Performance Regression Detector
Author: BbgnsurfTech

byBbgnsurfTech

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Deployment & DevOps

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

About

This skill automates the identification of performance regressions during the software delivery process, ensuring that new code changes do not negatively impact application speed or throughput. By integrating directly into CI/CD pipelines, it gathers performance data, applies statistical analysis to identify significant deviations, and flags threshold violations. It provides developers with actionable reports, including root cause analysis and trend visualizations, making it an essential tool for maintaining high-performance standards throughout the development lifecycle.

Key Features

3 GitHub stars
Detailed regression reporting with severity levels and root cause insights
Automated baseline comparison against historical performance data
Visual representation of performance trends across build history
Statistical analysis to identify significant performance deviations
Customizable threshold monitoring for response times and throughput

Use Cases

Detecting throughput degradation following a major code merge
Validating release readiness by comparing current performance against historical benchmarks
Identifying response time increases in the latest CI/CD build

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add bbgnsurftech/claude-skills-collection performance-regression-detector

For use in Claude.ai and ChatGPT

Download Skill

GitHub