使用 RFC 驅動的多智能體 DAG 執行模式，具備品質關卡、合併佇列及工作單元編排。適用於需要執行 RFC 驅動的多智能體執行，並搭配品質關卡與合併佇列的情境。
ralphinho-rfc-pipeline 技巧提供了一個結構化的、RFC 驅動的多智能體工作流程，用於協調由依賴關係圖 (DAG) 分解而成的大型功能。它最適合單次智能體執行無法處理，需拆分為多個可獨立驗證工作單元的情況。技巧定義了七個主要階段：從 RFC 輸入、DAG 分解，到單元指派、實作、驗證、合併整合，最後進行全系統驗證。每個工作單元遵循嚴格的規範，包含 ID、依賴關係、範圍、驗收測試、風險等級及復原計畫。此外，它還引入了複雜度分級（Tier 1 到 Tier 3），以區分從簡單的單一檔案編輯到涉及 schema、安全性或效能變更的高風險任務。該流程為每個單元強制執行內建品質管道 (研究、計畫、實作、測試、審查、可合併報告)，並加入合併佇列規則，確保絕不提交存在未解決依賴失敗的單元，且須在最新整合分支上重新基底。停滯的單元則會自動從佇列中移除、記錄發現、縮小範圍後重試。最終產出包括完整的 RFC 執行日誌、單元記分卡、依賴圖快照及整合風險摘要，為整個開發過程提供高度透明與追蹤性。
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/ralphinho-rfc-pipeline靈感來自 humanplane 風格的 RFC 分解模式與多單元編排工作流程。
當某個功能對於單次 Agent 傳遞來說太過龐大，必須拆分為可獨立驗證的工作單元時，請使用此技巧。
每個工作單元應包含：
iddepends_onscopeacceptance_testsrisk_levelrollback_plan如果單元停滯：
This repo contains 20 individual skills — each has its own dedicated page.
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.
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.
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.
Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.
Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.
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.
gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.
Example project-specific skill template based on a real production application.
Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
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.
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.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent
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.
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.
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.
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.
Extract frames or short clips from videos using ffmpeg.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Use when testing, fixing, or extending the OpenClaw Control UI GUI with Vitest + Playwright end-to-end checks, mocked Gateway WebSocket flows, mocked dashboard runs, screenshots/videos, or agent-verifiable browser proof.
Obra superpowers agent skills.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...
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.