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orch-build-mvp

根据设计文档或规范文档编排构建最小可行产品(MVP)——摄入文档,规划薄垂直切片,搭建首个端到端切片,然后通过 TDD 实现、审查和门控提交。用于将 SDD/PRD 转化为可运行的起点。

orch-build-mvp 是什么?

该技能用于将设计或规范文档(如 SDD、PRD、系统设计文档)转化为可运行的最小可行产品(MVP)。其核心机制是:首先解析文档,提取范围和特性列表,将其拆分为多个“薄垂直切片”——优先实现一个完整的端到端路径,而非先构建所有模型再构建所有视图。随后,利用 `orch-pipeline` 引擎和 GAN 评测框架(与 `gan-build` 命令集成)驱动迭代构建:将规范转换为测试基准和评估标准,然后通过生成器-评估器的循环进行 TDD 式开发,直至评分通过或收敛。该技能支持 Claude Code 等 AI 编码代理,可通过门控(切片计划和预提交)逐步推进,并将每个切片作为独立的 `feat:` 提交。此外,对于涉及安全触发器的切片,还会自动引入安全审查。

兼容平台✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/orch-build-mvp

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

orch-build-mvp 是做什么的?

参与者 · 动作 · 目标:orch · build · mvp。是对共享引擎的轻量封装,该引擎位于 orch-pipeline。

何时使用

  • 用户拥有 设计/规范文档(SDD、PRD、system_design),并希望从该文档启动一个可运行的垂直切片。
  • 将文档路径作为参数传入,例如 civicpulse/docs/SDD-v0.6.md。

操作设置

  • 默认尺寸下限: large —— 这是完整的流水线,包括 Scaffold 阶段。
  • 阶段掩码: 0(读取规范)→ 1 → 2(重负载)→ 3(搭建框架)→ 4 → 5 → 6。
  • 第一步(阶段 0 → 2): 读取文档;提取范围、已锁定的决策以及特性列表;将其排序为 薄垂直切片(优先实现一条端到端路径,而非先构建所有模型再构建所有视图)。阶段 3 负责搭建第一个切片。

工作原理

  1. 使用上述设置运行 orch-pipeline 引擎。
  2. 复用已有的 GAN 测试框架,而不是手动编写迭代循环:
    • 将 SDD 翻译为 gan-harness/spec.md + gan-harness/eval-rubric.md (这替代了 gan-planner 会生成的内容 —— 你已拥有规范)。
    • 通过 /gan-build "<一行简述>" --skip-planner 驱动构建 (默认值:--max-iterations 15、--pass-threshold 7.0、 --eval-mode playwright;对非 UI 切片使用 --eval-mode code-only)。
    • 该命令运行 gan-generator → gan-evaluator 循环,并将结果写入 gan-harness/feedback/feedback-NNN.md,直到评分通过或收敛。
  3. 在 门控 1(切片计划)和 门控 2(预提交)处停止。将搭建框架和每个切片作为独立的 feat: 提交。
  4. 为任何触及安全触发器的切片添加 security-reviewer。

示例

orch-build-mvp: civicpulse/docs/SDD-v0.6.md
→ 读取 SDD → 切片列表(垂直)→ 搭建切片 1  [门控 1:批准]
→ /gan-build --skip-planner(生成器 → 评估器循环)评分 vs 规范 → 审查
→ 提交 feat:  [门控 2:确认] → 下一个切片

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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