openspec-proposal-creation-cn

forztf/open-skilled-sdd · updated Apr 8, 2026

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$npx skills add https://github.com/forztf/open-skilled-sdd --skill openspec-proposal-creation-cn
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summary

遵循规范驱动开发方法,生成完整的变更提案。

skill.md

规范提案创建

遵循规范驱动开发方法,生成完整的变更提案。

快速开始

创建规范提案包含三类输出:

  1. proposal.md - 为什么、做什么、影响摘要
  2. tasks.json - 编号的实施清单
  3. spec-delta.md - 正式的需求变更(ADDED/MODIFIED/REMOVED)

基本流程:生成变更 ID → 脚手架目录 → 起草提案 → 编写规范差异 → 验证结构

工作流

复制此清单并跟踪进度:

规划进度:
- [ ] 第 1 步:审阅现有规范
- [ ] 第 2 步:生成唯一的变更 ID
- [ ] 第 3 步:生成目录结构
- [ ] 第 4 步:起草 proposal.md(为什么、做什么、影响摘要)
- [ ] 第 5 步:创建 tasks.json 实施清单
- [ ] 第 6 步:编写 spec-delta.md 规范差异(ADDED/MODIFIED/REMOVED)
- [ ] 第 7 步:验证提案结构
- [ ] 第 8 步:向用户展示并请求审批

第 1 步:审阅现有规范

在创建提案前,了解当前状态:

# 列出所有现有规范
find spec/specs -name "spec.md" -type f

# 列出进行中的变更以避免冲突
find spec/changes -maxdepth 1 -type d -not -path "*/archive"

# 搜索相关需求
grep -r "### Requirement:" spec/specs/

第 2 步:生成唯一的变更 ID

选择具描述性、URL 安全的标识符:

格式add-<feature>fix-<issue>update-<component>remove-<feature>

示例

  • add-user-authentication
  • fix-payment-validation
  • update-api-rate-limits
  • remove-legacy-endpoints

校验:检查是否冲突:

ls spec/changes/ | grep -i "<proposed-id>"

第 3 步:生成目录结构

按标准结构创建变更目录:

# 将 {change-id} 替换为实际 ID
mkdir -p spec/changes/{change-id}/specs/{capability-name}

示例

mkdir -p spec/changes/add-user-auth/specs/authentication

第 4 步:起草 proposal.md

templates/proposal.md 为起点。

必需章节

  • Why:驱动变更的问题或机会
  • What Changes:修改项清单
  • Impact:受影响的规范、代码、API、用户

语气:清晰、简洁、面向决策。避免不必要背景。

第 5 步:创建 tasks.json 实施清单

将实现拆分为具体、可测试的任务。使用 templates/tasks.json

格式

# 实施任务
```json
[
  {
    "number": 1,
    "category": "阶段 1:基础设施",
    "task": "环境搭建任务 - 数据库架构、依赖等",
    "steps": [
      { "step": "初始化 Git 仓库并配置 .gitignore", "completed": false },
      { "step": "创建并激活 Python 虚拟环境", "completed": false },
      { "step": "创建 requirements.txt 或 pyproject.toml 并安装依赖 (FastAPI, SQLAlchemy, Pydantic, Alembic 等)", "completed": false },
      { "step": "设计初始数据库 ER 图", "completed": false },
      { "step": "配置数据库连接字符串和环境变量 (.env)", "completed": false },
      { "step": "初始化 Alembic 迁移环境", "completed": false }
    ],
    "passes": false
  }
]


**最佳实践**- 每个任务可独立完成
- 为每个主要组件添加测试任务
- 为每个主要组件添加测试任务
- 包含测试与验证任务
- 按依赖排序(数据库先于 API 等)
- 通常 5-15 个任务;更多时应拆分
- 每次仅处理1个step

第 6 步:以 EARS 格式编写规范差异

这是最关键步骤。规范差异使用 EARS 格式(易于需求语法)。

完整 EARS 指南reference/EARS_FORMAT.md

差异操作

  • ## ADDED Requirements - 新增能力
  • ## MODIFIED Requirements - 行为变更(包含完整更新文本)
  • ## REMOVED Requirements - 弃用功能

基本需求结构

## ADDED Requirements

### Requirement: 用户登录
WHEN 用户提交有效凭据,
系统 SHALL 认证用户并创建会话。

#### Scenario: 登录成功
GIVEN 用户邮箱为 "[email protected]" 且密码为 "correct123"
WHEN 用户提交登录表单
THEN 系统创建已认证会话
AND 重定向至仪表盘

用于验证的模式reference/VALIDATION_PATTERNS.md

第 7 步:验证提案结构

在展示给用户前运行以下检查:

结构清单:
- [ ] 目录存在:`spec/changes/{change-id}/`
- [ ] proposal.md 包含 Why/What/Impact
- [ ] tasks.json 含编号任务列表(5-15 项)
- [ ] 规范差异包含操作标题(ADDED/MODIFIED/REMOVED)
- [ ] 需求遵循 `### Requirement: <name>` 格式
- [ ] 场景使用 `#### Scenario:` 格式(四个井号)

自动化检查

# 统计差异操作(应 > 0)
grep -c "## ADDED\|MODIFIED\|REMOVED" spec/changes/{change-id}/specs/**/*.md

# 验证场景格式(显示行号)
grep -n "#### Scenario:" spec/changes/{change-id}/specs/**/*.md

# 检查需求标题
grep -n "### Requirement:" spec/changes/{change-id}/specs/**/*.md

第 8 步:提交用户评审

清晰总结提案:

## Proposal Summary

**Change ID**:{change-id}
**Scope**:{简要描述}

**创建的文件**- spec/changes/{change-id}/proposal.md
- spec/changes/{change-id}/tasks.json
- spec/changes/{change-id}/specs/{capability}/spec-delta.md

**下一步**请评审提案。如认可或修正后,请回复 "openspec开发" 或 "按顺序完成任务" 开始实施。

进阶主题

EARS 格式细节:见 reference/EARS_FORMAT.md 验证模式:见 reference/VALIDATION_PATTERNS.md 完整示例:见 reference/EXAMPLES.md

常见模式

模式 1:新增功能提案

新增能力时:

  • 使用 ADDED Requirements 差异
  • 同时包含正向场景与错误处理
  • 在场景中考虑边界情况

模式 2:破坏性变更提案

修改既有行为时:

  • 使用 MODIFIED Requirements 差异
  • 包含完整更新后的需求文本
  • 在 proposal.md 中说明变更内容与原因
  • 在 tasks.json 中考虑迁移任务

模式 3:弃用提案

移除功能时:

  • 使用 REMOVED Requirements 差异
  • 在 proposal.md 中记录移除理由
  • 在 tasks.json 中包含清理任务
  • 在影响部分考虑用户迁移

反模式避免

不要

  • 跳过验证检查(务必运行 grep 模式)
  • 未先审阅现有规范就创建提案
  • 使用含糊的任务描述(如"修一下")
  • 编写不含场景的需求
  • 忽略错误处理场景
  • 在一个提案中混合多个无关变更

  • 在创建变更 ID 前检查冲突
  • 编写具体、可测试的任务
  • 同时包含正向与负向场景
  • 一个提案只处理一个关注点
  • 在展示前验证结构

文件模板

所有模板位于 templates/ 目录:

参考资料


Token 预算:此 SKILL.md 约 250 行,低于建议的 500 行上限。引用文件按需加载以逐步呈现。

how to use openspec-proposal-creation-cn

How to use openspec-proposal-creation-cn on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add openspec-proposal-creation-cn
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/forztf/open-skilled-sdd --skill openspec-proposal-creation-cn

The skills CLI fetches openspec-proposal-creation-cn from GitHub repository forztf/open-skilled-sdd and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/openspec-proposal-creation-cn

Reload or restart Cursor to activate openspec-proposal-creation-cn. Access the skill through slash commands (e.g., /openspec-proposal-creation-cn) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.460 reviews
  • William Agarwal· Dec 28, 2024

    openspec-proposal-creation-cn is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Chaitanya Patil· Dec 12, 2024

    We added openspec-proposal-creation-cn from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Mia Iyer· Dec 4, 2024

    Useful defaults in openspec-proposal-creation-cn — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Kabir Reddy· Nov 23, 2024

    I recommend openspec-proposal-creation-cn for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kabir Li· Nov 23, 2024

    openspec-proposal-creation-cn fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Kabir Anderson· Nov 19, 2024

    Keeps context tight: openspec-proposal-creation-cn is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Piyush G· Nov 3, 2024

    openspec-proposal-creation-cn reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Shikha Mishra· Oct 22, 2024

    openspec-proposal-creation-cn is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Kabir Jain· Oct 14, 2024

    Solid pick for teams standardizing on skills: openspec-proposal-creation-cn is focused, and the summary matches what you get after install.

  • Kabir Haddad· Oct 14, 2024

    openspec-proposal-creation-cn has been reliable in day-to-day use. Documentation quality is above average for community skills.

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