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ralphinho-rfc-pipeline

基于RFC驱动的多智能体DAG执行模式,配备质量门禁、合并队列和工作单元编排。当需要运行带有质量门禁和合并队列的RFC驱动多智能体执行时使用。

ralphinho-rfc-pipeline 是什么?

该技能实现了一种基于RFC(请求评论)驱动的多智能体DAG(有向无环图)执行模式,专为需要拆分为多个独立可验证工作单元的大型特性设计。它模仿humanplane风格的RFC分解模式和多单元编排工作流,支持完整的流水线阶段:从RFC接收、DAG分解、单元分配、实现、验证、合并队列集成到最终系统验证。每个工作单元包含ID、依赖关系、范围、验收测试、风险等级和回滚计划,并按照三个复杂度层级(Tier1-3)进行分类。质量流水线针对每个单元涵盖研究、实现计划、实现、测试、审查和合并就绪报告。该技能可集成到Claude Code、Cursor或Codex等支持多步骤执行的AI代理平台中,通过严格的合并队列规则和故障恢复机制确保复杂任务的稳定推进。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/ralphinho-rfc-pipeline

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打开一个已预加载此 Agent Skill 的新对话。

文档

Ralphinho RFC 流水线

灵感来源于 humanplane 风格的RFC分解模式和多单元编排工作流。

当某个特性对于单次智能体传递而言过大,必须拆分为独立可验证的工作单元时,请使用此技能。

流水线阶段

  1. RFC 接收
  2. DAG 分解
  3. 单元分配
  4. 单元实现
  5. 单元验证
  6. 合并队列与集成
  7. 最终系统验证

单元规范模板

每个工作单元应包含:

  • id
  • depends_on
  • scope
  • acceptance_tests
  • risk_level
  • rollback_plan

复杂度层级

  • 层级 1:孤立文件编辑,确定性测试
  • 层级 2:多文件行为变更,中等集成风险
  • 层级 3:模式/认证/性能/安全性变更

每单元质量流水线

  1. 研究
  2. 实现计划
  3. 实现
  4. 测试
  5. 审查
  6. 合并就绪报告

合并队列规则

  • 绝不合并存在未解决依赖失败的单元。
  • 始终将单元分支变基到最新的集成分支。
  • 每次排队合并后重新运行集成测试。

恢复

如果某个单元停滞:

  • 将其从活动队列中移除
  • 冻结调查结果
  • 重新生成更窄的单元范围
  • 使用更新后的约束重试

输出

  • RFC 执行日志
  • 单元评分卡
  • 依赖关系图快照
  • 集成风险摘要

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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