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benchmark

Use esta habilidade para medir linhas de base de desempenho, detectar regressões antes/depois de PRs e comparar alternativas de stack.

O que é benchmark?

A habilidade **benchmark** permite que desenvolvedores e agentes de IA meçam, monitorem e comparem o desempenho de aplicações web de forma sistemática. Ela suporta quatro modos de operação: desempenho de página (com métricas reais do navegador como LCP, CLS, INP), desempenho de API (latências p50/p95/p99), desempenho de build (tempos de compilação, HMR, testes) e comparações antes/depois para detectar regressões em Pull Requests. Os resultados são salvos como arquivos JSON em `.ecc/benchmarks/` e são versionados pelo Git, permitindo que toda a equipe compartilhe e acompanhe a evolução das métricas ao longo do tempo. A habilidade se integra facilmente com CI/CD para executar automaticamente em cada PR, e pode ser combinada com ferramentas como `/canary-watch` para monitoramento pós-deploy e `/browser-qa` para checklists completos antes do lançamento.

Funciona com~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/benchmark

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Documentação

Benchmark — Linha de Base de Desempenho e Detecção de Regressão

Quando Usar

  • Antes e depois de um PR para medir o impacto no desempenho
  • Definindo linhas de base de desempenho para um projeto
  • Quando usuários relatarem "está lento"
  • Antes de um lançamento — garantir que você atenda às metas de desempenho
  • Comparando sua stack com alternativas

Como Funciona

Modo 1: Desempenho de Página

Mede métricas reais do navegador via navegador MCP:

1. Navegue para cada URL alvo
2. Meça os Core Web Vitals:
   - LCP (Largest Contentful Paint) — alvo < 2,5s
   - CLS (Cumulative Layout Shift) — alvo < 0,1
   - INP (Interaction to Next Paint) — alvo < 200ms
   - FCP (First Contentful Paint) — alvo < 1,8s
   - TTFB (Time to First Byte) — alvo < 800ms
3. Meça os tamanhos dos recursos:
   - Peso total da página (alvo < 1MB)
   - Tamanho do bundle JS (alvo < 200KB gzip)
   - Tamanho do CSS
   - Peso das imagens
   - Peso dos scripts de terceiros
4. Conte as requisições de rede
5. Verifique recursos que bloqueiam a renderização

Modo 2: Desempenho de API

Faz benchmark de endpoints de API:

1. Acesse cada endpoint 100 vezes
2. Meça: latência p50, p95, p99
3. Acompanhe: tamanho da resposta, códigos de status
4. Teste sob carga: 10 requisições simultâneas
5. Compare contra metas de SLA

Modo 3: Desempenho de Build

Mede o ciclo de feedback de desenvolvimento:

1. Tempo de build a frio
2. Tempo de hot reload (HMR)
3. Duração do conjunto de testes
4. Tempo de verificação TypeScript
5. Tempo de lint
6. Tempo de build Docker

Modo 4: Comparação Antes/Depois

Execute antes e depois de uma alteração para medir o impacto:

/benchmark baseline    # salva as métricas atuais
# ... faça alterações ...
/benchmark compare     # compara com a linha de base

Saída:

| Métrica | Antes | Depois | Variação | Veredito |
|---------|-------|--------|----------|----------|
| LCP | 1,2s | 1,4s | +200ms | AVISO: WARN |
| Bundle | 180KB | 175KB | -5KB | ✓ MELHOR |
| Build | 12s | 14s | +2s | AVISO: WARN |

Saída

Armazena linhas de base em .ecc/benchmarks/ como JSON. Rastreado pelo Git para que a equipe compartilhe as linhas de base.

Integração

  • CI: execute /benchmark compare em cada PR
  • Combine com /canary-watch para monitoramento pós-implantação
  • Combine com /browser-qa para checklist completo antes do lançamento

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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