performance-testing

This skill enables Claude to design, execute, and analyze performance tests using the performance-test-suite plugin. It is activated when the user requests load testing, stress testing, spike testing, or endurance testing, and when discussing performance metrics such as response time, throughput, and error rates. It identifies performance bottlenecks related to CPU, memory, database, or network issues. The plugin provides comprehensive reporting, including percentiles, graphs, and recommendations.

1.00x

Quality

53%

Does it follow best practices?

Impact

100%

1.00x

Average score across 9 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./backups/skills-migration-20251108-070147/plugins/testing/performance-test-suite/skills/performance-test-suite/SKILL.md

Evaluation results

100%

Performance Testing Strategy for API Launch

Test type selection and parameter configuration

Criteria

Without context

With context

Load test identified

100%

Target users specified

100%

Ramp-up time specified

100%

Test duration specified

100%

Response time metric

100%

Throughput metric

100%

Error rate metric

100%

Multiple configurations

100%

Realistic usage patterns

100%

Results inform next test

100%

Bottleneck categories mentioned

100%

Analyze Performance Test Results and Generate Report

Bottleneck identification and report generation

Criteria

Without context

With context

Percentile reporting

100%

Response time analysis

100%

Throughput analysis

100%

Error rate analysis

100%

CPU bottleneck identified

100%

Database bottleneck identified

100%

Memory trend noted

100%

Graph or visualization

100%

Recommendations present

100%

KPI summary

100%

Breaking point identified

100%

Design Performance Tests for a Viral Campaign Launch

Iterative multi-test strategy design

Criteria

Without context

With context

Spike test identified

100%

Endurance test identified

100%

Spike ramp parameters

100%

Endurance duration

100%

Target user counts

100%

Response time metric

100%

Error rate metric

100%

Memory metric

100%

Multiple test types

100%

Test sequencing rationale

100%

Realistic scenario design

100%

Pass/fail criteria

100%

Payments API Capacity Limits Before Product Launch

Stress test design and breaking point identification

Criteria

Without context

With context

Stress test identified

100%

Gradually increasing load

100%

Breaking point identification method

100%

Response time metric

100%

Error rate metric

100%

Throughput metric

100%

At least one additional metric category

100%

Concrete pass/fail thresholds

100%

Target user counts specified

100%

Degradation vs failure distinction

100%

Test duration specified

100%

Performance Testing an E-Commerce Platform's Core User Journey

Realistic user flow scenario design

Criteria

Without context

With context

User flow design

100%

Traffic distribution

100%

Load test type chosen

100%

Response time metric

100%

Throughput metric

100%

Error rate metric

100%

Additional metric breadth

100%

Per-endpoint breakdown

100%

Target user count specified

100%

Ramp-up specified

100%

Test duration specified

100%

Bottleneck interpretation

100%

Validating API Performance After a Database Schema Migration

Post-deployment performance regression validation

Criteria

Without context

With context

Baseline comparison methodology

100%

Matching test conditions

100%

Percentile reporting in report

100%

Visualization present

100%

Pass/fail verdict

100%

Per-metric thresholds

100%

Recommendations included

100%

Response time metrics present

100%

Error rate metric present

100%

Throughput metric present

100%

KPI summary section

100%

Long-Running Stability Investigation for a Document Processing Service

Endurance test design for long-running service stability

Criteria

Without context

With context

Endurance test type named

100%

Extended duration configured

100%

Memory metric specified

100%

Gradual degradation detection method

100%

Response time metric included

100%

Error rate metric included

100%

Database metric included

100%

Concurrent users configured

100%

Realistic traffic pattern

100%

Pass/fail threshold defined

100%

Recommendations present

100%

test_config.json produced

100%

Performance Analysis for a Distributed Media Streaming Platform

Network bottleneck identification and cross-service report

Criteria

Without context

With context

Network bottleneck identified

100%

Percentile analysis included

100%

Visualization present

100%

Error rate analysis

100%

Throughput analysis

100%

CPU and memory ruled out

100%

Holistic metric coverage

100%

Specific recommendations

100%

Executive summary or KPI section

100%

Per-service breakdown

100%

Root cause analysis

100%

Performance Trend Report for a SaaS Search Service

Multi-run performance trend analysis and iterative strategy

Criteria

Without context

With context

Percentile trend analysis

100%

Trend visualization

100%

Throughput trend analyzed

100%

Error rate trend analyzed

100%

Remaining bottleneck identified

100%

Bottleneck category named

100%

Holistic metric coverage

100%

Recommendations provided

100%

KPI or executive summary

100%

Results inform next test

100%

next_test_config.json valid

100%

Improvement quantified

100%

Repository: jeremylongshore/claude-code-plugins-plus-skills
Commit: c8a915c

Evaluated: about 1 month ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Performance Testing Strategy for API Launch Analyze Performance Test Results and Generate Report Design Performance Tests for a Viral Campaign Launch Payments API Capacity Limits Before Product Launch Performance Testing an E-Commerce Platform's Core User Journey Validating API Performance After a Database Schema Migration Long-Running Stability Investigation for a Document Processing Service Performance Analysis for a Distributed Media Streaming Platform Performance Trend Report for a SaaS Search Service

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