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verification-loop

Um sistema abrangente de verificação para sessões do Claude Code. Use ao verificar uma sessão do Claude Code.

O que é verification-loop?

O Verification Loop Skill é uma ferramenta de verificação abrangente projetada especificamente para sessões do Claude Code. Ele guia o usuário através de seis fases de verificação: compilação, verificação de tipos, lint, testes, segurança e revisão de diff. Cada fase possui comandos de terminal pré-definidos para Node.js (npm/pnpm) e Python (pyright/ruff), garantindo que a qualidade do código atenda aos padrões exigidos antes de criar um Pull Request (PR). O skill gera um relatório final (Build, Types, Lint, Tests, Security, Diff) indicando se o projeto está "PRONTO" ou "NÃO PRONTO" para PR. Ele também suporta modo contínuo com checkpoints mentais e complementa hooks de pós-ferramenta, fornecendo uma revisão mais profunda. Ideal para desenvolvedores que usam Claude Code, este skill automatiza e padroniza a verificação de qualidade, economizando tempo e reduzindo erros.

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

Perguntar na sua IA favorita

Abre um novo chat com esta habilidade de agente já pré-carregada.

Documentação

Skill de Loop de Verificação

Um sistema abrangente de verificação para sessões do Claude Code.

Quando Usar

Invoque este skill:

  • Após concluir um recurso ou mudança significativa de código
  • Antes de criar um PR
  • Quando quiser garantir que os portões de qualidade sejam aprovados
  • Após refatoração

Fases de Verificação

Fase 1: Verificação de Compilação

# Verifica se o projeto compila
npm run build 2>&1 | tail -20
# OU
pnpm build 2>&1 | tail -20

Se a compilação falhar, PARE e corrija antes de continuar.

Fase 2: Verificação de Tipos

set -o pipefail
# Projetos TypeScript
npx --no-install tsc --noEmit 2>&1 | head -30

# Projetos Python
pyright . 2>&1 | head -30

Relate todos os erros de tipo. Corrija os críticos antes de continuar.

Fase 3: Verificação de Lint

# JavaScript/TypeScript
npm run lint 2>&1 | head -30

# Python
ruff check . 2>&1 | head -30

Fase 4: Suíte de Testes

# Executa testes com cobertura
npm run test -- --coverage 2>&1 | tail -50

# Verifica limite de cobertura
# Meta: mínimo de 80%

Relate:

  • Total de testes: X
  • Aprovados: X
  • Reprovados: X
  • Cobertura: X%

Fase 5: Varredura de Segurança

# Verifica segredos
grep -rn "sk-" --include="*.ts" --include="*.js" . 2>/dev/null | head -10
grep -rn "api_key" --include="*.ts" --include="*.js" . 2>/dev/null | head -10

# Verifica console.log
grep -rn "console.log" --include="*.ts" --include="*.tsx" src/ 2>/dev/null | head -10

Fase 6: Revisão de Diff

# Mostra o que mudou
git diff --stat
git diff HEAD~1 --name-only

Revise cada arquivo alterado para:

  • Mudanças não intencionais
  • Tratamento de erros ausente
  • Casos extremos potenciais

Formato de Saída

Após executar todas as fases, produza um relatório de verificação:

RELATÓRIO DE VERIFICAÇÃO
=========================

Compilação: [APROVADO/REPROVADO]
Tipos:      [APROVADO/REPROVADO] (X erros)
Lint:       [APROVADO/REPROVADO] (X avisos)
Testes:     [APROVADO/REPROVADO] (X/Y aprovados, Z% cobertura)
Segurança:  [APROVADO/REPROVADO] (X problemas)
Diff:       [X arquivos alterados]

Geral:      [PRONTO/NÃO PRONTO] para PR

Problemas a Corrigir:
1. ...
2. ...

Modo Contínuo

Para sessões longas, execute a verificação a cada 15 minutos ou após mudanças importantes:

Defina um checkpoint mental:
- Após completar cada função
- Após finalizar um componente
- Antes de passar para a próxima tarefa

Execute: /verify

Integração com Hooks

Este skill complementa hooks PostToolUse, mas fornece verificação mais aprofundada. Os hooks capturam problemas imediatamente; este skill oferece uma revisão abrangente.

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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