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產品能力規劃

將產品需求文件(PRD)意圖、路線圖需求或產品討論轉化為可執行的能力計劃,明確揭露約束條件、不變量、介面與未決決策,避免跨服務工作啟動時的模糊規劃。

產品能力規劃 是什麼?

這個技能「產品能力規劃」專為開發者與 AI 代理(如 Claude Code、Codex、Cursor)設計,能將模糊的產品意圖轉化為明確的工程約束。它的核心價值在於填補「要做什麼」與「實作前必須確定什麼」之間的鴻溝,特別適合跨多個服務、儲存庫或團隊的功能開發。技能會引導使用者從產品需求、現有架構文件和交付限制中提取關鍵約束,產出一個類似 SRS(軟體需求規格)的能力合約,包含明確的參與者、介面、狀態轉換與非目標。最終的輸出格式包含「能力重申」「約束」「實化合約」「非目標」「未決問題」與「交接指示」六個區塊,可直接銜接後續的專案流程、API 設計或測試驅動開發工作流。這個技能強調「不要發明產品真相」,要求明確標記未解決的問題,讓隱藏的假設變得可持續、可重用,避免在程式碼審查或實作過程中重複發現相同的隱含約束。

相容平台✓Claude Code✓Codex CLI✓Cursor✓OpenCode
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/product-capability

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

產品能力規劃 是做什麼的?

這個技能將產品意圖轉化為明確的工程約束。

請在下列情況使用:問題不在於「我們該建什麼?」而在於「開始實作前,究竟必須確定什麼?」

何時使用

  • 已有 PRD、路線圖項目、討論或創辦人筆記,但實作約束仍然隱含未明
  • 某功能跨越服務、儲存庫或團隊,需要在編寫程式碼前先建立能力合約
  • 產品意圖明確,但架構、資料、生命週期或政策影響仍模糊不清
  • 資深工程師在審查時持續重複相同的隱含假設
  • 你需要一個可重複使用的產出物,能夠跨越不同環境與工作階段

標準產出物

如果儲存庫已有永久的產品背景檔案(如 PRODUCT.md、docs/product/ 或程式規格目錄),請直接更新該處。

如果尚未存在任何能力說明檔案,請使用以下範本建立一份:

  • docs/examples/product-capability-template.md

目標不是增加另一層規劃堆疊,而是讓隱含的能力約束變得可持續、可重用。

不可妥協的規則

  • 不要發明產品真相。請明確標記未解決的問題。
  • 區分使用者可見的承諾與實作細節。
  • 明確指出哪些是固定政策、哪些是架構偏好、哪些仍待決定。
  • 如果需求與現有儲存庫約束衝突,請清楚說明,而非粉飾太平。
  • 偏好一份可重複使用的能力產出物,勝過零散的備忘錄。

輸入資料

僅讀取必要的資訊:

  1. 產品意圖
    • 議題、討論、PRD、路線圖筆記、創辦人訊息
  2. 當前架構
    • 相關儲存庫文件、合約、結構定義、路由、現有工作流程
  3. 現有能力背景
    • PRODUCT.md、設計文件、RFC、遷移筆記、運作模型文件
  4. 交付限制
    • 驗證、計費、合規、上線、向後相容、效能、審查政策

核心工作流程

1. 重申能力

將需求壓縮成一句精確的描述:

  • 使用者或操作者是誰
  • 此功能上線後,什麼新能力會存在
  • 因為這個能力,什麼結果會改變

如果這句描述很薄弱,實作就會偏離方向。

2. 解析能力約束

提取在實作前必須成立的約束:

  • 業務規則
  • 範圍邊界
  • 不變量
  • 信任邊界
  • 資料所有權
  • 生命週期轉換
  • 上線/遷移需求
  • 失敗與復原期望

這些往往是只存在於資深工程師記憶中的東西。

3. 定義實作面向的合約

產出一個 SRS 風格的能力計劃,包含:

  • 能力摘要
  • 明確的非目標
  • 參與者與接觸面
  • 必要狀態與轉換
  • 介面/輸入/輸出
  • 資料模型影響
  • 安全性/計費/政策約束
  • 可觀測性與運維需求
  • 阻擋實作的未決問題

4. 轉化為執行

最後給出精確的交接指示:

  • 可直接實作
  • 需要先進行架構審查
  • 需要先釐清產品需求

若有幫助,可指向下一個 ECC 原生工作流:

  • project-flow-ops
  • workspace-surface-audit
  • api-connector-builder
  • dashboard-builder
  • tdd-workflow
  • verification-loop

輸出格式

請按以下順序回傳結果:

能力
- 一段話的重申

約束
- 固定規則、不變量與邊界

實化合約
- 參與者
- 接觸面
- 狀態與轉換
- 介面/資料影響

非目標
- 此工作流明確不負責的項目

未決問題
- 阻擋實作的障礙或仍需做出的產品決策

交接
- 接下來應發生什麼,以及應由哪個 ECC 工作流接手

理想的成果

  • 產品意圖已具體到無需在 PR 進行到一半時重新發現隱含約束即可實作。
  • 工程審查擁有可持續使用的產出物,而非依賴記憶或 Slack 背景資訊。
  • 產出的計劃可在 Claude Code、Codex、Cursor、OpenCode 與 ECC 2.0 規劃介面中重複使用。

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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