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orch-fix-defect

버그 재현, 수정, 코드 리뷰 및 게이트 커밋까지 각 단계를 적절한 ECC 에이전트에 위임하여 버그 수정을 오케스트레이션합니다. 기존 동작이 깨지거나 잘못된 경우 사용하세요.

orch-fix-defect란 무엇인가요?

`orch-fix-defect`는 버그 수정 전 과정을 자동화하는 AI 에이전트 스킬입니다. 기존 기능이 잘못 동작하거나, 에러가 발생하거나, 크래시가 나는 상황에서 사용합니다. 이 스킬은 버그를 재현하는 실패하는 회귀 테스트를 먼저 작성하고, 테스트가 통과할 때까지 코드를 수정한 후, 코드 리뷰를 거쳐 게이트 커밋까지 진행하는 파이프라인을 오케스트레이션합니다. `orch-change-feature`(동작 변경)나 `orch-add-feature`(새 기능)와 달리, `orch-fix-defect`는 '깨진 동작'을 '올바른 동작'으로 복원하는 데 특화되어 있습니다. 내부적으로는 `orch-pipeline` 엔진을 사용하며, 필요 시 `code-explorer`로 근본 원인을 분석하거나 `security-reviewer`로 보안 검토를 추가할 수 있습니다. Cursor, Claude Code 등 다양한 개발 환경에서 에이전트를 활용하여 버그 수정 워크플로를 일관되고 효율적으로 관리할 수 있습니다.

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

즐겨 사용하는 AI에게 물어보기

이 에이전트 스킬이 미리 로드된 새 채팅을 엽니다.

문서

orch-fix-defect은(는) 무엇을 하나요?

Actor · action · target: orch · fix · defect. 공유 엔진에 대한 얇은 래퍼: orch-pipeline 참조.

사용 시기

  • 무언가 고장난 경우: 잘못된 출력, 에러, 충돌, 회귀.
  • 다음 스킬과 구분하세요:
    • 동작은 올바르지만 다르게 만들고 싶다면 → orch-change-feature.
    • 기능이 아직 존재하지 않는다면 → orch-add-feature.

작업 설정

  • 기본 크기 하한: small (종종 사소함).
  • 단계 마스크: 0 → (근본 원인이 명확하지 않거나 standard+인 경우에만 light 2) → 4 → 5 → 6. 연구(1)는 보통 건너뜁니다.
  • 첫 번째 동작(단계 4): 버그를 새로운 실패 테스트(회귀 테스트)로 재현한 후, 통과할 때까지 수정합니다. 먼저 버그가 존재함을 입증하는 것이 수정과 단순 조정을 구분짓는 요소입니다.

작동 방식

  1. 위 설정으로 orch-pipeline 엔진을 실행합니다.
  2. 근본 원인이 명확하지 않으면, 빨간 테스트 전에 code-explorer로 범위를 좁히고; 빌드 실패 시 build-error-resolver / /build-fix로 에스컬레이션합니다.
  3. 게이트 1(계획이 생성된 경우에만)과 게이트 2(커밋 전)에서 중지합니다.
  4. 결함이 보안에 민감한 경로에 있다면 security-reviewer를 추가합니다.

예시

orch-fix-defect: empty NWS 응답 시 폴러가 충돌하는 버그
→ 충돌을 재현하는 실패하는 테스트 작성 → 통과하도록 수정
→ 코드 리뷰 → 커밋  [GATE 2: 확인]   (커밋 메시지: 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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