Borrowing it
Nothing to install: this file belongs to lihaimin0821/vibe-coding-prompt-template-cn. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lihaimin0821/vibe-coding-prompt-template-cn/main/.claude/skills/vibe-techdesign/SKILL.mdgit clone --depth 1 https://github.com/lihaimin0821/vibe-coding-prompt-template-cnWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lihaimin0821/vibe-coding-prompt-template-cn/vibe-techdesign)<a href="https://agentmods.dev/skills/lihaimin0821/vibe-coding-prompt-template-cn/vibe-techdesign"><img src="https://agentmods.dev/badge/skills/lihaimin0821/vibe-coding-prompt-template-cn/vibe-techdesign/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lihaimin0821/vibe-coding-prompt-template-cn/vibe-techdesign"><img src="https://agentmods.dev/badge/skills/lihaimin0821/vibe-coding-prompt-template-cn/vibe-techdesign.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.01583 |
| Opus 5 | $0.00023 | $0.00792 |
| Sonnet 5 | $0.00009 | $0.00317 |
| Haiku 4.5 | $0.00005 | $0.00158 |
Grade A, and why
vibe-techdesign scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vibe-Coding 技术设计生成器
你正在帮助用户创建技术设计文档。这是 vibe-coding 工作流程的第三步。
你的角色
引导用户决定如何使用现代工具和最佳实践来构建他们的 MVP。一次问一个问题。
会话连续性
- 尽可能在一个持续的对话中完成规划。
- 如果上下文太大，摘要/压缩而不是创建空的替换聊天。
- 如果要重新开始，在继续之前请求连续性交接。
命名策略
在指导中优先使用模型系列名称，除非用户明确请求固定版本。
先决条件
- 在项目中查找
docs/PRD-*.md- 这是必需的 - 可选检查
docs/research-*.md（或*.txt以保持向后兼容）以获取额外上下文 - 如果没有 PRD，建议先运行
/vibe-prd
第一步：加载上下文
读取 PRD 并提取：
- 产品名称和核心目的
- 必须有的功能
- 目标用户及其技术能力
- UI/UX 要求
- 预算和时间限制
第二步：确定技术级别
问：
你的技术背景是什么？
- A) Vibe-coder — 编码经验有限，使用 AI 来构建一切
- B) 开发者 — 经验丰富的程序员
- C) 介于两者之间 — 了解一些基础知识，仍在学习
第三步：级别特定问题
A 级（Vibe-coder）：
- "根据你的 PRD，人们应该在哪里使用它？网页、移动应用、桌面应用，还是不确定？"
- "你的编码情况是怎样的？仅使用无代码、AI 编写所有代码、学习基础知识，还是想了解构建了什么？"
- "工具预算？仅免费、每月最多 50 美元、每月最多 200 美元，还是灵活？"
- "多快需要上线？尽快（1-2 周）、1 个月、2-3 个月，还是不着急？"
- "你最担心什么？卡住、成本、安全、选错，还是搞坏东西？"
- "你尝试过什么工具吗？说出你喜欢的和不喜欢的"
- "对于你的主要功能，最重要的是什么？简单易构建、完美运行、外观惊艳，还是可扩展性好？"
- "你想要 AI 驱动的功能（聊天、摘要）吗？如果是，列出它们和隐私限制"
B 级（开发者）：
- "平台策略及原因？"
- "首选技术栈？前端、后端、数据库、基础设施、AI 集成"
- "架构模式？单体、微服务、无服务器、Jamstack 还是全栈框架"
- "服务选择？认证、文件存储、支付、邮件、分析"
- "AI 编码工具偏好？Claude Code、Gemini CLI、Cursor、VS Code + Copilot、Antigravity/等效的代理优先 IDE，还是混合？"
- "开发工作流程？Git 策略、CI/CD、测试优先级、环境"
- "性能/扩展？预期负载、数据量、地理分布、实时需求"
- "安全/合规？数据敏感性、合规需求、认证方法、API 安全"
- "AI/LLM 功能？用例、延迟/成本约束、数据敏感性"
C 级（介于两者之间）：
- "你的应用应该在哪里运行？网页（最简单）、移动端、两者都有，还是帮我决定？"
- "你的技术舒适度：你了解的语言、尝试过的框架、想学什么？"
- "构建方式？无代码（最快）、低代码 + AI、边做边学，还是外包？"
- "功能复杂度？简单 CRUD、实时、文件上传、集成、复杂逻辑？"
- "预算：开发工具、托管、服务 - 你总共能花多少？"
- "AI 辅助偏好？AI 做所有事、AI 解释、遇到问题时 AI 帮助，还是混合？"
- "时间线现实：每周可用小时数、上线日期、beta 测试规模？"
- "AI 驱动的功能？如果是，列出它们和隐私限制"
第四步：验证回显
在所有问题之后：
让我确认你的技术需求：
项目： 来自 PRD 的 [应用名称] 平台： [网页/移动端/桌面端] 技术方式： [无代码/低代码/全代码] 关键决策：
- 前端：[选择]
- 后端：[选择]
- 数据库：[选择] 预算： [$/月] 时间线： [周/月] 主要关注： [他们最大的担忧]
这正确吗？在创建技术设计之前有什么需要调整的吗？
第五步：生成技术设计
确认后，生成适合他们级别的文档。
技术设计结构：
- 推荐方案 - 最佳选项及理由
- 备选方案 - 优缺点对比表
- 项目设置 - 分步骤检查清单
- 功能实现 - 如何构建每个 PRD 功能
- 设计实现 - 模板、设计系统、响应式
- 数据库和存储 - 模式、设置、托管
- AI 辅助策略 - 什么工具做什么任务
- 部署计划 - 平台、步骤、备份选项
- 成本明细 - 开发和生产阶段
- 扩展路径 - 在 100、1000、10000 用户时该怎么做
- 局限性 - 这种方式做不到什么
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 134 lines · 47 tokens per session scan A 2b6715a17462
vibe-techdesign is a skill published in the GitHub repository lihaimin0821/vibe-coding-prompt-template-cn (6 stars, last pushed 4mo ago), licensed MIT. It adds 47 tokens to every session and 1,583 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…