Agent skill

Performance Testing

by vibeeval in vibeeval/vibecosystem

Load testing with k6/Artillery, response time thresholds, memory leak detection, N+1 query detection, and CI integration.

MITAuto-check passedTesting & QA

Install Performance Testing

skills CLI
$ npx skills add vibeeval/vibecosystem --skill performance-testing -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install vibeeval/vibecosystem performance-testing --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/vibeeval/vibecosystem.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/performance-testing .claude/skills/performance-testing && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
performance-testing
GitHub stars
531
Token cost
~1.4k tokens
SKILL.md length
118 words
Files
1
Skills in repo
144
Repo updated
First seen
Licence
MIT

At a glance

Load testing with k6/Artillery, response time thresholds, memory leak detection, N+1 query detection, and CI integration.

  • Tasks that involve Load testing
  • SKILL.md covers k6 Script Patterns, Load Test Types, Threshold Definitions and CI Integration (GitHub Actions…, plus 4 more sections
  • Calls node and git; needs LHCI_GITHUB_APP_TOKEN
  • Tasks that involve Performance optimization

What it does

Performance Testing is an agent skill from vibeeval/vibecosystem. Load testing with k6/Artillery, response time thresholds, memory leak detection, N+1 query detection, and CI integration.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering Load testing and Performance optimization. The repository describes itself as: AI software team for Claude Code - 138 agents, 295 skills, 73 hooks. Self-learning, multi-agent swarm, autonomous skill evolution. The licence is MIT.

When your agent uses it

  • Tasks that involve Load testing
  • Tasks that involve Performance optimization

Example prompts

  • “/performance-testing”

Requirements

  • Node.js
  • A credential in LHCI_GITHUB_APP_TOKEN

What it can do on your machine

Read from SKILL.md and the folder at commit 3b763b1. 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

    Shell commands in SKILL.md call:

    • node
    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LHCI_GITHUB_APP_TOKEN

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

Context cost

Performance Testing loads about 1.4k tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 118 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~35
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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

Auto-check passed

The automated check found no risky patterns in SKILL.md.

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from vibeeval/vibecosystem at commit 3b763b1, republished under its MIT licence (© vibeeval). 118 words, ~1,365 tokens.

Download SKILL.mdSave it as .claude/skills/performance-testing/SKILL.md (or your agent's skills folder).
name
performance-testing
description
Load testing with k6/Artillery, response time thresholds, memory leak detection, N+1 query detection, and CI integration.

Performance Testing

k6 Script Patterns

Basic scenario with stages
javascript
// k6 run load-test.js
import http from 'k6/http'
import { check, sleep } from 'k6'

export const options = {
  stages: [
    { duration: '30s', target: 10 },   // ramp up
    { duration: '1m',  target: 50 },   // hold load
    { duration: '30s', target: 0 },    // ramp down
  ],
  thresholds: {
    http_req_duration: ['p(95)<200', 'p(99)<500'],
    http_req_failed:   ['rate<0.01'],   // < 1% error rate
  },
}

export default function () {
  const res = http.get('https://api.example.com/users')
  check(res, {
    'status is 200':       (r) => r.status === 200,
    'response time < 200ms': (r) => r.timings.duration < 200,
  })
  sleep(1)
}
POST with auth
javascript
export default function () {
  const payload = JSON.stringify({ email: 'test@example.com', password: 'secret' })
  const headers = { 'Content-Type': 'application/json' }
  const res = http.post(`${BASE_URL}/auth/login`, payload, { headers })
  const token = res.json('token')

  http.get(`${BASE_URL}/profile`, {
    headers: { Authorization: `Bearer ${token}` },
  })
}

Load Test Types

TypeDurationTarget VUPurpose
Smoke1 min1-5Verify script works, no regressions
Load30 minexpected peakNormal production conditions
Stress60 min2-3x peakFind breaking point
Spike2 min10x peak → 0Sudden traffic burst behavior
Soak4-8 hours80% peakMemory leaks, degradation over time

Threshold Definitions

javascript
export const options = {
  thresholds: {
    // Response time
    http_req_duration: ['p(95)<200', 'p(99)<500', 'avg<100'],

    // Error rate
    http_req_failed: ['rate<0.01'],   // < 1%

    // Custom metric for specific endpoint
    'http_req_duration{name:login}': ['p(95)<300'],

    // Checks pass rate
    checks: ['rate>0.99'],
  },
}

CI Integration (GitHub Actions + k6)

yaml
# .github/workflows/perf.yml
name: Performance Tests
on:
  pull_request:
    branches: [main]

jobs:
  k6:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Run k6 smoke test
        uses: grafana/k6-action@v0.3.1
        with:
          filename: tests/perf/smoke.js
          flags: --out json=results.json
      - name: Upload results
        uses: actions/upload-artifact@v4
        with:
          name: k6-results
          path: results.json

Memory Leak Detection (Node.js)

Heap snapshot approach
bash
# Start with --inspect
node --inspect --expose-gc server.js

# In Chrome DevTools → Memory → Take heap snapshot
# Run load, take another snapshot
# Compare: growing retained objects = leak
Programmatic detection
javascript
import v8 from 'v8'

function checkHeap(label) {
  const stats = v8.getHeapStatistics()
  console.log(`[${label}] Heap used: ${Math.round(stats.used_heap_size / 1024 / 1024)}MB`)
}

setInterval(() => checkHeap('monitor'), 30_000)
Common leak patterns to watch
javascript
// BAD: event listener never removed
emitter.on('data', handler)   // grows on every request

// GOOD: cleanup in teardown
emitter.on('data', handler)
return () => emitter.off('data', handler)

// BAD: unbounded cache
const cache = {}
cache[userId] = data   // never evicted

// GOOD: bounded cache
import LRU from 'lru-cache'
const cache = new LRU({ max: 1000, ttl: 1000 * 60 * 5 })

N+1 Query Detection

pg_stat_statements (PostgreSQL)
sql
-- Enable extension
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

-- Find repetitive queries during a load test window
SELECT
  query,
  calls,
  mean_exec_time,
  total_exec_time
FROM pg_stat_statements
WHERE calls > 100
ORDER BY calls DESC
LIMIT 20;
Query logging (development)
javascript
// Prisma: log all queries
const prisma = new PrismaClient({
  log: ['query'],
})

// Detect N+1: same query fired N times in a request
// Fix: use include/select or DataLoader
DataLoader pattern (N+1 fix)
javascript
import DataLoader from 'dataloader'

const userLoader = new DataLoader(async (ids) => {
  const users = await db.user.findMany({ where: { id: { in: ids } } })
  return ids.map(id => users.find(u => u.id === id))
})

// In resolver — batches automatically
const user = await userLoader.load(post.authorId)

Web Vitals / Lighthouse CI

yaml
# .github/workflows/lhci.yml
- name: Lighthouse CI
  run: |
    npm install -g @lhci/cli
    lhci autorun
  env:
    LHCI_GITHUB_APP_TOKEN: ${{ secrets.LHCI_GITHUB_APP_TOKEN }}
json
// lighthouserc.json
{
  "ci": {
    "assert": {
      "assertions": {
        "categories:performance": ["error", { "minScore": 0.8 }],
        "first-contentful-paint": ["error", { "maxNumericValue": 2000 }],
        "largest-contentful-paint": ["error", { "maxNumericValue": 2500 }],
        "cumulative-layout-shift": ["error", { "maxNumericValue": 0.1 }]
      }
    }
  }
}

Trend Tracking

Store k6 results to Grafana/InfluxDB for trend visualization:

bash
k6 run --out influxdb=http://localhost:8086/k6 load-test.js

Or export JSON and compare baselines:

bash
k6 run --out json=results-$(git rev-parse --short HEAD).json load-test.js

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

Files

Just SKILL.md in skills/performance-testing of vibeeval/vibecosystem.

Open the folder on GitHubat commit 3b763b1

Compare with similar skills

Performance Testing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Performance Testing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Performance Testing this skillvibeeval/vibecosystem531—~1.4kAutomated safety check: PassMIT
Performanceaiskillstore/marketplace4301 repos~2.6kAutomated safety check: PassNone
Performance EngineerFerroxLabs/wayland608—~5.1kAutomated safety check: PassApache-2.0
HTTP Load Profilerzebbern/claude-code-guide4.6k—~1.6kAutomated safety check: NotesMIT
Performance Profilerborghei/Claude-Skills874—~1.8kAutomated safety check: PassMIT
Afrexai Performance EngineeringLeoYeAI/openclaw-master-skills2.2k—~7.1kAutomated safety check: PassMIT

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Categories

Questions about Performance Testing

What does Performance Testing do?

Load testing with k6/Artillery, response time thresholds, memory leak detection, N+1 query detection, and CI integration. Performance Testing is an agent skill from vibeeval/vibecosystem. Load testing with k6/Artillery, response time thresholds, memory leak detection, N+1 query detection, and CI integration.

When should I use Performance Testing?

Performance Testing fits situations like: tasks that involve Load testing; tasks that involve Performance optimization.

How do I install Performance Testing in Claude Code?

Run `npx skills add vibeeval/vibecosystem --skill performance-testing -a claude-code`. Or copy the skill folder (skills/performance-testing in vibeeval/vibecosystem) into .claude/skills/performance-testing in your project. Claude Code loads it when a task matches its description.

How do I install Performance Testing in Codex?

Run `npx skills add vibeeval/vibecosystem --skill performance-testing -a codex`. Or copy the skill folder (skills/performance-testing in vibeeval/vibecosystem) into .agents/skills/performance-testing in your project. Codex loads it when a task matches its description.

Can I use Performance Testing in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vibeeval/vibecosystem --skill performance-testing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performance-testing, .gemini/skills/performance-testing, .github/skills/performance-testing and .opencode/skills/performance-testing in your project.

What does Performance Testing need to run?

Going by SKILL.md and its folder, Performance Testing needs the command-line tools its instructions call (node and git) and credentials named LHCI_GITHUB_APP_TOKEN. Our summary lists: Node.js; A credential in LHCI_GITHUB_APP_TOKEN.

Does Performance Testing access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Performance Testing safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Performance Testing use?

Performance Testing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Performance Testing use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Performance Testing?

Skills that share tags, products or a category with Performance Testing: Performance (aiskillstore/marketplace, 430 stars), Performance Engineer (FerroxLabs/wayland, 608 stars), HTTP Load Profiler (zebbern/claude-code-guide, 4.6k stars) and Performance Profiler (borghei/Claude-Skills, 874 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Performance Testing?

vibeeval (a GitHub user) maintains it in vibeeval/vibecosystem, which has 531 GitHub stars. The repository holds 144 skills in this directory. The repository was last updated on August 8, 2026.

Source: vibeeval/vibecosystem on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.