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Sdlc Design

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TsCarpe
sdlc-design

Produces the technical design document (design.md) from the confirmed requirement digest: solution alternatives, data model, tiered interface contracts, shared-asset inventory with delivery ownership, decision table (C-constraint/H-assumption), and implementation slicing constraints handed to task frameworks like Trellis. Use when the requirement digest is confirmed and design is due, or the user says 技术设计、详细设计、概要设计、出设计、设计文档、接口契约、D 表、方案骨架、切分约束、sdlc-design. 用法:/sdlc-design 需求名

Overview

PublisherTsCarpe
Repositoryclaude-sdlc-skills
Skill namesdlc-design
Stars
65
Forks
0
Bundled files
9
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 9 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by TsCarpe on GitHub. Read the source before you install it.

Installation

Install the Sdlc Design AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/TsCarpe/claude-sdlc-skills/tree/main/skills/sdlc-design
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/TsCarpe/claude-sdlc-skills.git /tmp/claude-sdlc-skills
mkdir -p .claude/skills
cp -r /tmp/claude-sdlc-skills/skills/sdlc-design .claude/skills/sdlc-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sdlc Design in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sdlc Design on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sdlc Design is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

技术设计(sdlc-design)

把已确认的需求共识(sdlc-intent 三件套)翻译成技术设计文档 design.md——供三方消费:sdlc-gate 评审、任务框架拆分执行、sdlc-test cases 并行推导。设计写成文档本身就是发现过程:契约、决策、公共资产在人能逐行核对的粒度上定死,下游切片免现场设计。

前置依赖:codegraph MCP(存量勘察;缺失时降级定向 grep + 读文件);mysql MCP(只读核对表结构,可选)。

路由(进入时先判)

读 sdlc/<需求名>/intake/ 最新 digest 头「风险分级」:

  • C 级 → 不产 design.md,产一页 sdlc/<需求名>/design/plan.md(逐接口方案,骨架见 references/design-template.md「C 级轻量方案」),随后走 /sdlc-gate <需求名> C 档主会话自查;放行后才可开发
  • A/B 级 → 继续;B 级按 mini 骨架产出(裁剪规则见 design-template 末节)
  • digest 不存在 → 停,先跑 sdlc-intent——设计的输入是共识版需求,不是原文速读
  • 已存在 design.md 且头部有 > 平台定稿: 锚点行(sdlc-sync pull-dev-bundle 拉回的平台定稿)→ 拒绝本地增量修订:该设计已在平台定稿,本地改动即口径漂移;引导用户走平台 design_rev / 变更单,修订定稿后 /sdlc-sync pull-dev-bundle <需求名> only:design 拉回。例外:用户显式要求重开时——警告「将脱离平台定稿基线,平台侧后续修订与本文件无法对账」,确认后允许重写,重写落盘时删除锚点行(本地文件回归普通设计,下次 pull 按无锚点路径比对)
  • 已存在 design.md 且用户未要求重开 → 读头部输入锚点(digest/audit/pm-checklist 三文件日期)与各文件最新一份比对:全部一致则在其上增量修订,任一更新即按增量修订处理并提示口径漂移、确认是否重审

Q 表定位规则

Q 表(问题/当前假设/阻塞范围,编号 确认.Q-xx)的载体按序定位:

  1. parent prd §6 已有 Q 表(大需求三段式链路)→ 复用,design 头部注明来源,增量项追加
  2. 无 prd(轻量链路)→ 本 skill 在 design 头部生成并维护:来源 = pm-checklist 未答复项 + digest §假设清单「假设」类条目(推断类不入表——推断有原文推导链,不算未决口径)

前置闸(任一未过按处置执行,不带病设计)

闸判据处置
1. Q 表硬阻塞存在阻塞写接口核心逻辑的未决口径被锁功能点照常按「当前假设」产出,契约/D 表相应行标 「锁定待拍板(确认.Q-xx)」;不得拒绝启动整个设计、不得把锁定扩大到未阻塞功能点(未决口径只锁对应功能点,不阻塞全局)
2. 分级已拍板digest 头风险分级处于提议态(未拍板)停,先请人拍板(拿不准从高)
3. tier 只升不降存量勘察发现影响面证据(公共组件/对外契约/并发一致性)且当前低于 A 级回写 digest 头升级并附证据;cases 已产出须同步 cases 头,issues 已产出同步 issues 头;按新级产出

流程

复制此 checklist 跟踪进度:

设计进度:
- [ ] Step 1: 前置闸三道 + 输入定位(digest / audit / pm-checklist / Q 表载体 / 项目规范源)
- [ ] Step 2: 存量勘察(现有接口/Req/组件/表结构)
- [ ] Step 3: 按 references/design-template.md 产出 design.md(A 全量 / B mini)
- [ ] Step 4: 齐套自检(A/B 下表六项;C 按 C 模板自检)
- [ ] Step 5: 落盘 + 🔒 暂停等确认点②定稿

Step 1 输入:intake 三件套 + 项目规范源(.trellis/spec/ 或 dev_standards/ 等项目自建规范目录,读不到则注明规范降级)+ ER 基线(如有)。

Step 2 存量勘察:契约必须贴现状不悬空——读现有接口/Req/组件/表结构后落笔。MCP 优先(完全限定名 codegraph:codegraph_explore、mysql:mysql_query);codegraph 缺失降级定向 grep + 读文件,mysql 缺失按设计内声明的表结构(均如实注明降级)。

Step 3 读取 references/design-template.md 按骨架产出(A 全量 / B mini / C 轻量方案);大需求落位与任务框架交接规则读取 references/trellis-handoff.md。

Step 4 齐套自检(漏项即返工,反馈循环)。C 级不套用下表六项,按 design-template「C 级轻量方案」自检(头部四项 + 逐接口表完整、验证命令可执行):

#检查
1D 表八类别显式决策(「不适用」也要写明;类型标 C 约束/H 假设,H 含接受条件)
2公共资产六类齐套 + 每项归属列(骨架切片先行的依据)
3接口契约每行挂 F 编号 + 口径来源;被锁行标「锁定待拍板」
4切分约束三件:骨架切片先行声明 / 横切核验矩阵 / 共享物归属
5audit 🔴/🟡 问题去向逐条有落点(已承接 / 转 Q 表 / 本期不做+理由)
6Q 表就位(复用注明来源 prd,或已按定位规则生成)

Step 5 落盘 + 🔒 暂停。落盘路径:A/B 轻量 = sdlc/<需求名>/design/design.md;C 级 = sdlc/<需求名>/design/plan.md(一页);大需求走任务框架 = parent 任务目录(如 Trellis .trellis/tasks/<task>/design.md,见 trellis-handoff.md)。确认点② 措辞:

设计产物已生成于 <路径>(A/B = design.md;C = plan.md),请逐行核对(确认点②定稿——ack 是定稿信号,不构成质量放行;放行唯一口径 = sdlc-gate issues 头「评审状态=已放行」)。同时测试用例应从 intake 三件套并行独立推导(/sdlc-test cases <需求名>,生成时禁止读本设计——交叉审查依赖用例在场,不做「设计先行、用例后补」降级档)。两线定稿后运行 /sdlc-gate <需求名> 开评审;gate 放行后才可拆分开发(guard_dev 开发入口校验)。C 级例外:cases 可缺失,plan.md 产出后直接走 /sdlc-gate C 档自查;/sdlc-test dev 前补最小 cases(P0 + 双向追踪表)。

设计纪律

  • 备选方案红线:至少一个关键决策写 Alternatives(选择/弃选/trade-off/依据功能点)——无备选、无 trade-offs 的设计是 implementation manual,不如不写
  • 决策类型 C 约束 / H 假设;H 必写接受条件(按什么标准判定假设成立、何时调整)
  • 不重复项目通用规范约定,只收本需求域新增/扩展项
  • 公共组件清单是脚手架不是合同:切片期调整组件接口不算偏差、不需回写(豁免仅限组件接口)

边界

  • 只产设计产物(A/B design.md;C design/plan.md),不做任务编排(建任务/拆 subtask/排期归任务框架;拆分规则随 §7 实施切分约束交付,见 trellis-handoff.md)
  • 不评审(设计评审归 sdlc-gate);单点决策存疑走 sdlc-doubt 旁路
  • 不替代 sdlc-intent:需求侧口径冲突回需求侧裁决,禁止设计期静默择一

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Sdlc Design AI skill do?

Produces the technical design document (design.md) from the confirmed requirement digest: solution alternatives, data model, tiered interface contracts, shared-asset inventory with delivery ownership, decision table (C-constraint/H-assumption), and implementation slicing constraints handed to task frameworks like Trellis. Use when the requirement digest is confirmed and design is due, or the user says 技术设计、详细设计、概要设计、出设计、设计文档、接口契约、D 表、方案骨架、切分约束、sdlc-design. 用法:/sdlc-design 需求名

Why use Sdlc Design on TypingMind?

Because you install it once and use it with any model. Sdlc Design is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sdlc Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/TsCarpe/claude-sdlc-skills/tree/main/skills/sdlc-design. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Sdlc Design?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sdlc Design?

As many as you like. As long as a model supports skills, you can use Sdlc Design with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sdlc Design AI skill free?

Yes. It is published on GitHub by TsCarpe under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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