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orch-fix-defect

バグの再現、修正、レビュー、ゲート付きコミットまでをECCエージェントに委譲して修正をオーケストレーションします。既存の動作が壊れている場合や間違っている場合に使用します。

orch-fix-defect とは？

`orch-fix-defect` は、バグ修正のワークフロー全体を自動化するAIエージェントスキルです。このスキルは、バグを再現する失敗テスト（回帰テスト）の作成から始め、テストが通るようにコードを修正し、コードレビューを経て、ゲート付きコミットを行うまでの各フェーズを、適切なECC（ Expert Coding Companion）エージェントに委譲します。これにより、人間の開発者は各ステップを手動で実行する必要がなくなり、修正プロセスが効率化されます。主な動作設定として、フェーズマスク（0→4→5→6）を使用し、通常はリサーチフェーズをスキップします。根本原因が不明瞭な場合には、`code-explorer` を用いて調査し、ビルドエラーが発生した場合には `build-error-resolver` にエスカレーションします。このスキルは `orch-pipeline` エンジンの薄いラッパーであり、`orch-change-feature`（振る舞いの変更）や `orch-add-feature`（新機能追加）とは異なり、既存の動作が壊れている場合に特化しています。セキュリティに関わる欠陥の場合は、`security-reviewer` を追加することも可能です。

対応✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/orch-fix-defect
オリジナルを見る→すべてのスキルを見る

お気に入りのAIに質問する

このエージェントスキルを事前に読み込んだ状態で新しいチャットを開きます。

OpenAIChatGPTClaudeClaudeGeminiGeminiGrokGrokPerplexityPerplexityDeepSeekDeepSeek

ドキュメント

orch-fix-defect は何をしますか？

Actor · action · target: orch · fix · defect。共有エンジン orch-pipeline 上の薄いラッパーです。

使用すべき時

  • 何かが 壊れている：誤った出力、エラー、クラッシュ、リグレッション。
  • 関連スキルとの区別：
    • 振る舞いは正しいが変更したい場合 → orch-change-feature。
    • その機能がまだ存在しない場合 → orch-add-feature。

動作設定

  • デフォルトのサイズフロア: small（多くの場合 trivial）。
  • フェーズマスク: 0 → （根本原因が不明瞭または standard+ の場合のみ light 2）→ 4 → 5 → 6。リサーチ（1）は通常スキップされます。
  • 最初のアクション（フェーズ4）: バグを 新しい失敗テスト（回帰テスト）として再現し、テストが通るまで修正します。バグの存在を最初に証明することが、修正と微調整を区別するポイントです。

仕組み

  1. 上記設定で orch-pipeline エンジンを実行します。
  2. 根本原因が不明瞭な場合、レッドテストの前に code-explorer でスコープを絞り込みます。ビルドエラーが発生した場合は build-error-resolver / /build-fix にエスカレーションします。
  3. ゲート1（計画が生成された場合のみ）と ゲート2（コミット前）で停止します。
  4. 欠陥がセキュリティ上重要なパスにある場合は、security-reviewer を追加します。

例

orch-fix-defect: poller crashes on empty NWS response
→ write failing test reproducing the crash → fix to green
→ code-review → commit  [GATE 2: confirm]   (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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