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orch-refine-code

在保持行為不變的前提下進行重構：確認測試通過，重構程式碼，維持測試通過，審查後提交。在需要改善結構但不改變行為時使用。

orch-refine-code 是什麼？

這個技能用於自動化「行為保持重構（behavior-preserving refactor）」流程，包含提取模組、移除重複、清理死碼、減少巢狀結構或重新命名以提升清晰度。它透過共用引擎 `orch-pipeline` 運作，並以 `refactor:` 的提交格式進行閘門控制提交。支援的階段遮罩為 0→2（規劃重構）→4（保持通過）→5→6，且不會撰寫新的行為測試，而是依賴現有測試套件作為安全網。此技能特別適用於開發工具如 Claude Code、Cursor 或 Codex，能確保結構改善的同時行為完全不變。

相容平台✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/orch-refine-code
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說明文件

orch-refine-code 是做什麼的？

Actor · action · target：orch · refine · code。是 orch-pipeline 中共用引擎的精簡包裝。

使用時機

  • 相同行為，更好的結構：提取模組、移除重複、清除死碼、減少巢狀、重新命名以提升清晰度。
  • 與同系列技能區分：如果行為有任何變更，則不應使用此技能（應改用 orch-change-feature / orch-fix-defect）。

操作設定

  • 預設規模下限： 標準 — 重構會觸及多個檔案。
  • 階段遮罩： 0 → 2（規劃重構）→ 4（保持通過）→ 5 → 6。不會撰寫新的行為測試 — 現有測試套件是安全網。
  • 第一步（階段 4）： 確認相關測試存在且在修改程式碼前為通過狀態；若測試覆蓋率不足，先新增特徵測試（characterization tests）。然後以小步驟進行重構，每步後重新執行測試。

運作方式

  1. 使用上述設定執行 orch-pipeline 引擎。
  2. 對於死碼/重複清理，委派給 refactor-cleaner agent（它會執行 knip / depcheck / ts-prune 並安全移除）。
  3. 在閘門 1（重構計劃）和閘門 2（提交前）暫停。
  4. 以 refactor: 提交 — 變更必須是行為中立的。

範例

orch-refine-code: 從 poller.py 中提取 NWS HTTP 客戶端
→ 確認測試通過 → 規劃提取  [閘門 1：批准]
→ 以小步驟移動，測試始終通過 → 程式碼審查
→ 提交 refactor:  [閘門 2：確認]

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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