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orch-fix-defect

Orquestra a correção de um bug — reproduzindo-o como um teste de regressão com falha, corrigindo até ficar verde, revisando e commitando com gate — delegando cada fase ao agente ECC correspondente. Use quando o comportamento existente estiver quebrado ou incorreto.

O que é orch-fix-defect?

O skill `orch-fix-defect` coordena o fluxo completo de correção de um defeito de software, delegando cada fase a agentes especializados da arquitetura ECC. Primeiro, ele garante que o bug seja reproduzido como um teste de regressão com falha (fase 4) — isso separa uma correção genuína de um ajuste superficial. Em seguida, o agente corrige o código até que o teste fique verde, passa por uma revisão de código (fase 5) e, por fim, realiza um commit gerenciado (fase 6), parando nos Gates 1 (plano) e 2 (pré-commit) para validação. Se a causa raiz não for óbvia, o skill aciona o agente `code-explorer` para escopo, e pode incluir `security-reviewer` em caminhos sensíveis à segurança. Ele é útil para cenários de erro, crash ou regressão, diferenciando-se dos skills `orch-change-feature` (comportamento correto, mas diferente) e `orch-add-feature` (funcionalidade inexistente). Suporte para ambientes de desenvolvimento onde a automação de pipelines de correção de bugs é necessária.

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

O que orch-fix-defect faz?

Ator · ação · alvo: orch · fix · defect. Wrapper fino sobre o mecanismo compartilhado em orch-pipeline.

Quando Usar

  • Algo está quebrado: saída incorreta, um erro, uma falha, uma regressão.
  • Distinguir dos skills irmãos:
    • comportamento está correto, mas você quer diferente → orch-change-feature.
    • a capacidade ainda não existe → orch-add-feature.

Configurações de Operação

  • Tamanho mínimo padrão: pequeno (frequentemente trivial).
  • Máscara de fase: 0 → (light 2 apenas se a causa raiz não for óbvia ou standard+) → 4 → 5 → 6. Pesquisa (1) geralmente é pulada.
  • Primeiro movimento (fase 4): reproduzir o bug como um novo teste com falha (teste de regressão) e então corrigir até ficar verde. Provar que o bug existe primeiro é o que separa uma correção de um ajuste.

Como Funciona

  1. Executa o mecanismo orch-pipeline com as configurações acima.
  2. Se a causa raiz não estiver clara, escopá-la com code-explorer antes do teste vermelho; escalar quebras de build para build-error-resolver / /build-fix.
  3. Parar no Gate 1 (apenas se um plano foi produzido) e Gate 2 (pré-commit).
  4. Adicionar security-reviewer se o defeito estiver em um caminho sensível à segurança.

Exemplo

orch-fix-defect: poller falha ao receber resposta NWS vazia
→ escrever teste com falha que reproduz a falha → corrigir até ficar verde
→ revisão de código → commit  [GATE 2: confirmar]   (commit: fix:)

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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