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performance-regression-detector skill

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This skill automatically detects performance regressions in CI/CD by analyzing metrics, comparing baselines, and reporting potential bottlenecks.

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill performance-regression-detector

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: detecting-performance-regressions
description: |
  This skill enables Claude to automatically detect performance regressions in a CI/CD pipeline. It analyzes performance metrics, such as response time and throughput, and compares them against baselines or thresholds. Use this skill when the user requests to "detect performance regressions", "analyze performance metrics for regressions", or "find performance degradation" in a CI/CD environment. The skill is also triggered when the user mentions "baseline comparison", "statistical significance analysis", or "performance budget violations". It helps identify and report performance issues early in the development cycle.
---

## Overview

This skill automates the detection of performance regressions within a CI/CD pipeline. It utilizes various methods, including baseline comparison, statistical analysis, and threshold violation checks, to identify performance degradation. The skill provides insights into potential performance bottlenecks and helps maintain application performance.

## How It Works

1. **Analyze Performance Data**: The plugin gathers performance metrics from the CI/CD environment.
2. **Detect Regressions**: It employs methods like baseline comparison, statistical analysis, and threshold checks to detect regressions.
3. **Report Findings**: The plugin generates a report summarizing the detected performance regressions and their potential impact.

## When to Use This Skill

This skill activates when you need to:
- Identify performance regressions in a CI/CD pipeline.
- Analyze performance metrics for potential degradation.
- Compare current performance against historical baselines.

## Examples

### Example 1: Identifying a Response Time Regression

User request: "Detect performance regressions in the latest build. Specifically, check for increases in response time."

The skill will:
1. Analyze response time metrics from the latest build.
2. Compare the response times against a historical baseline.
3. Report any statistically significant increases in response time that exceed a defined threshold.

### Example 2: Detecting Throughput Degradation

User request: "Analyze throughput for performance regressions after the recent code merge."

The skill will:
1. Gather throughput data (requests per second) from the post-merge CI/CD run.
2. Compare the throughput to pre-merge values, looking for statistically significant drops.
3. Generate a report highlighting any throughput degradation, indicating a potential performance regression.

## Best Practices

- **Define Baselines**: Establish clear and representative performance baselines for accurate comparison.
- **Set Thresholds**: Configure appropriate thresholds for identifying significant performance regressions.
- **Monitor Key Metrics**: Focus on monitoring critical performance metrics relevant to the application's behavior.

## Integration

This skill can be integrated with other CI/CD tools to automatically trigger regression detection upon new builds or code merges. It can also be combined with reporting plugins to generate detailed performance reports.

Overview

This skill automates detection of performance regressions inside a CI/CD pipeline. It compares current metrics like response time and throughput to baselines or thresholds, flags statistically significant deviations, and summarizes likely impacts. Use it to catch degradation early and feed actionable findings back into the release process.

How this skill works

The skill pulls performance metrics from CI/CD runs or monitoring exports and normalizes them for comparison. It applies baseline comparison, threshold checks, and basic statistical significance tests to identify regressions. Results are packaged into a concise report that highlights affected metrics, magnitude of change, and confidence level for each finding.

When to use it

After running performance tests in a CI/CD job to validate a new build
When a pull request or merge may impact latency or throughput
To verify performance against a scheduled baseline or performance budget
When you need automated alerts for threshold or budget violations
Before releasing to production to prevent regressions slipping through

Best practices

Establish representative baselines using stable, known-good builds
Choose thresholds that balance sensitivity and noise to avoid false positives
Monitor a focused set of key metrics (latency p50/p95, throughput, error rate, resource usage)
Include contextual metadata (commit, environment, test type) with metric samples
Run statistically meaningful sample sizes and use repeated runs for noisy tests

Example use cases

Detect a statistically significant increase in API response time after a merge
Identify a drop in throughput following a dependency upgrade or configuration change
Automatically fail a CI job when performance budget thresholds are exceeded
Compare current build metrics against a 30-day baseline to spot slow drifts in performance
Generate a performance regression report for an incident postmortem

FAQ

What data sources are supported?

Any CI/CD or monitoring output that provides time-series metrics (logs, Prometheus, CSV exports). The skill normalizes common formats for analysis.

How does it decide if a change is significant?

It uses configurable threshold checks plus simple statistical tests (e.g., t-test or nonparametric checks) and reports confidence along with the magnitude of change.