Performance Testing

What it does

When your agent uses it

• Planning load tests
• Benchmarking APIs
• Identifying performance bottlenecks

Example prompts

• “Use the performance-testing skill to profile application performance under load using k6, Artillery, or JMeter to measure latency, throughput, and…”
• “/performance-testing”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1DEFINE SLOs: p95 response time, throughput, error rate targets
2. 2IDENTIFY critical paths: revenue flows, high-traffic pages, key APIs
3. 3CREATE realistic scenarios: user journeys, think time, varied data
4. 4EXECUTE with monitoring: CPU, memory, DB queries, network
5. 5ANALYZE bottlenecks and fix before production

What it can do on your machine

Read from SKILL.md and the folder at commit 829d030. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 1 file in scripts/, which the agent can run.

  Shell commands in SKILL.md call:

  • node

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Performance Testing loads about 2.4k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 65 tokens; SKILL.md has 609 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~65

When it runs · the whole SKILL.md, loaded when a task matches

~2.4k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~2.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from proffesor-for-testing/agentic-qe at commit 829d030, republished under its MIT licence (© proffesor-for-testing). 609 words, ~2,381 tokens.

name

performance-testing

description

Profiles application performance under load using k6, Artillery, or JMeter to measure latency, throughput, and error rates. Use when planning load tests, stress tests, soak tests, benchmarking APIs, or identifying performance bottlenecks.

category

specialized-testing

priority

high

tokenEstimate

1100

agents

qe-performance-tester, qe-quality-analyzer, qe-production-intelligence

implementation_status

optimized

optimization_version

1

last_optimized

2025-12-02

quick_reference_card

true

tags

performance, load-testing, stress-testing, scalability, k6, bottlenecks

trust_tier

3

export const options = {
  thresholds: {
    http_req_duration: ['p(95)<200'],  // 95% < 200ms
    http_req_failed: ['rate<0.01'],     // < 1% failures
  },
};

// Realistic distribution
// 40% browse, 30% search, 20% details, 10% checkout
export default function () {
  const action = Math.random();
  if (action < 0.4) browse();
  else if (action < 0.7) search();
  else if (action < 0.9) viewProduct();
  else checkout();

  sleep(randomInt(1, 5)); // Think time
}

// BAD: 100 orders = 101 queries
const orders = await Order.findAll();
for (const order of orders) {
  const customer = await Customer.findById(order.customerId);
}

// GOOD: 1 query
const orders = await Order.findAll({ include: [Customer] });

// performance-test.js
import http from 'k6/http';
import { check, sleep } from 'k6';

export const options = {
  stages: [
    { duration: '1m', target: 50 },   // Ramp up
    { duration: '3m', target: 50 },   // Steady
    { duration: '1m', target: 0 },    // Ramp down
  ],
  thresholds: {
    http_req_duration: ['p(95)<200'],
    http_req_failed: ['rate<0.01'],
  },
};

export default function () {
  const res = http.get('https://api.example.com/products');
  check(res, {
    'status is 200': (r) => r.status === 200,
    'response time < 200ms': (r) => r.timings.duration < 200,
  });
  sleep(1);
}

# GitHub Actions
- name: Run k6 test
  uses: grafana/k6-action@v0.3.0
  with:
    filename: performance-test.js

Load: 1,000 users | p95: 180ms | Throughput: 5,000 req/s
Error rate: 0.05% | CPU: 65% | Memory: 70%

Load: 1,000 users | p95: 3,500ms ❌ | Throughput: 500 req/s ❌
Error rate: 5% ❌ | CPU: 95% ❌ | Memory: 90% ❌

// Comprehensive load test
await Task("Load Test", {
  target: 'https://api.example.com',
  scenarios: {
    checkout: { vus: 100, duration: '5m' },
    search: { vus: 200, duration: '5m' },
    browse: { vus: 500, duration: '5m' }
  },
  thresholds: {
    'http_req_duration': ['p(95)<200'],
    'http_req_failed': ['rate<0.01']
  }
}, "qe-performance-tester");

// Bottleneck analysis
await Task("Analyze Bottlenecks", {
  testResults: perfTest,
  metrics: ['cpu', 'memory', 'db_queries', 'network']
}, "qe-performance-tester");

// CI integration
await Task("CI Performance Gate", {
  mode: 'smoke',
  duration: '1m',
  vus: 10,
  failOn: { 'p95_response_time': 300, 'error_rate': 0.01 }
}, "qe-performance-tester");

aqe/performance/
├── results/*       - Test execution results
├── baselines/*     - Performance baselines
├── bottlenecks/*   - Identified bottlenecks
└── trends/*        - Historical trends

const perfFleet = await FleetManager.coordinate({
  strategy: 'performance-testing',
  agents: [
    'qe-performance-tester',
    'qe-quality-analyzer',
    'qe-production-intelligence',
    'qe-deployment-readiness'
  ],
  topology: 'sequential'
});

node -e "
const fs = require('fs');
const h = JSON.parse(fs.readFileSync('.claude/skills/performance-testing/run-history.json'));
h.runs.push({date: new Date().toISOString().split('T')[0], scenario: 'load', p95_ms: P95, throughput_rps: RPS, error_rate_pct: ERR});
fs.writeFileSync('.claude/skills/performance-testing/run-history.json', JSON.stringify(h, null, 2));
"

© proffesor-for-testing, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in assets/skills/performance-testing of proffesor-for-testing/agentic-qe.

• SKILL.md
• config.json
• evals/performance-testing.yaml
• references/k6-patterns.md
• run-history.json
• schemas/output.json
• scripts/validate-config.json

Open the folder on GitHubat commit 829d030