The 12 Essential Prompts Every Vibe Coder Needs

Vibe coding with LLMs has completely changed how we build software. The secret? Talking to your AI coding assistant in clear, precise language. Learning to write effective prompts takes practice, but having a collection of battle-tested prompts can dramatically speed up your workflow.

Here are the 12 core prompts every vibe coder should master. These aren't just copy-paste templates. Understanding the structure and intent behind each one will help you communicate more effectively with an AI assistant in any situation.

Part 1: Planning and architecture (prompts 1-3)

1. The PRD generator: start with clarity

Before you write a single line of code, you need a clear product requirements document. This prompt forces you to think through every key element:

When to use: at the very start of any new project or major feature.

Prompt:

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我想构建【你的想法】。

在编写任何代码之前，创建一份 PRD，包含：

1. 问题陈述：这解决了什么问题？谁有这个问题？
2. 用户故事：5-7 个故事，格式为"作为【用户】，我想要【行动】，以便【收益】"
3. 核心功能（仅 MVP）：v1 版本必须有什么？要狠心砍掉不必要的。
4. 不在范围内：什么功能留到 v2？
5. 技术需求：技术栈、集成、数据模型、认证需求
6. 成功指标：我们如何知道它有效？
7. 待解决问题：在构建之前需要决定什么？

要具体，不要泛泛而谈。

Why it works: this prompt prevents the classic mistake of jumping straight into code without understanding the problem. The instruction "be ruthless about cutting" (要狠心砍掉) is especially powerful: it forces you to slash scope hard, which is essential for shipping fast.

2. The codebase archaeologist: understand before you build

Inherited a codebase, or coming back to your own code after a few months? This prompt helps you grasp the architecture quickly.

When to use: joining a new project, getting into a team codebase, or before adding a major feature to existing code.

Prompt:

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分析这个代码库，告诉我：

1. 架构模式（MVC、Clean 等）
2. 数据流：用户输入 → API → 数据库 → UI
3. 关键文件：路由在哪？模型在哪？认证在哪？业务逻辑在哪？
4. 关键依赖及其作用
5. 添加新功能时需要遵循的模式（从代码中展示示例）
6. 潜在问题（安全、性能、过时的模式）
7. 如果我想添加【功能】，我需要修改哪些文件？

先完整阅读文件。不要假设。

Why it works: the instruction "read the files in full first. Don't assume" (先完整阅读文件。不要假设) is critical. It stops the AI from making assumptions based on common patterns and forces it to analyse your actual codebase structure.

3. The implementation planner: think before you code

This may be the single most important prompt for preventing messy, hard-to-maintain code.

When to use: after the PRD is approved, but before writing any implementation code.

Prompt:

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我需要实现这个【PRD 或功能】。

在编写代码之前，创建一个实现计划：

阶段 1 - 分析：
- 这会影响哪些现有代码？
- 需要哪些新文件？
- 任务之间的依赖关系？

阶段 2 - 数据：
- 数据库结构变更
- 新的 API 端点
- 验证规则

阶段 3 - 后端：
- 业务逻辑
- 错误处理
- 边缘情况

阶段 4 - 前端：
- 需要的组件
- 状态管理
- 用户反馈

阶段 5 - 集成：
- 各部分如何连接
- 测试方法
- 回滚计划

对于每个阶段：复杂度（简单/中等/复杂）和具体文件。

不要编写代码。我需要先批准这个计划。

Why it works: the instruction "don't write code" (不要编写代码) is powerful. It forces both you and the AI to think through the whole implementation before committing code. That avoids the common trap of discovering an architectural problem halfway through implementation.

Part 2: Scope management and debugging (prompts 4-5)

4. The scope guardian: do less, ship faster

Feature creep kills projects. This prompt helps you cut scope ruthlessly and ship sooner.

When to use: when planning a feature, when you want to add "just one more feature", or when the timeline slips.

Prompt:

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我正在构建【功能】。做我无情的范围守护者。

1. 最小可行版本：能提供价值的绝对最简单版本是什么？
2. 暂不构建：锦上添花的功能、<5% 用户的边缘情况、过早优化
3. 完成定义：什么标准 = 可以发布？
4. 时间陷阱：什么会比预期花费 10 倍时间？
5. 唯一的事：如果我只能交付一个能力，应该是什么？

要激进。我以后总能添加更多。

Why it works: the instruction "be aggressive" (要激进) turns your AI into a strict product manager who challenges scope. The "one thing" (唯一的事) question is especially powerful: it forces you to identify the core value proposition.

5. The debugging detective: escape the loop

Spent hours debugging the same problem? This prompt gets you out of the loop by systematically exploring new possibilities.

When to use: when you've tried several fixes that didn't work, or you're going in circles while debugging.

Prompt:

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我陷入了调试循环。Bug 是：【描述它】

你已经尝试了很多不起作用的方法；先分析什么没有帮助。在建议修复之前：

1. 列出 5-7 个不同的新可能原因。考虑：
   - 数据问题，而不是代码？
   - 环境/配置问题？
   - 竞态条件/时序问题？
   - 缓存问题？
   - Bug 完全在其他地方？

2. 按可能性排序
3. 对于前 2 个：添加诊断日志来证明/反驳每个。先不要修复。
4. 只有在我们确认原因后才修复。

Why it works: this prompt prevents the "try random fixes" approach. By forcing diagnosis before fixing, it saves time and helps you understand the root cause instead of applying band-aid solutions.

Part 3: Code quality and maintenance (prompts 6-7)

6. The tech debt auditor: clean up as you go

Technical debt piles up silently. This prompt helps you identify and prioritise clean-up work.

When to use: monthly maintenance sprints, before a major refactor, or when code quality is slowing you down.

Prompt:

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审计这个代码库的技术债务。给我一个可操作的优先级列表。

查找：
1. 应该提取的重复代码
2. 死代码（未使用的文件、函数、导出）
3. 过时的模式、废弃的 API
4. 缺失的错误处理
5. 安全隐患（硬编码密钥、SQL 拼接、缺失验证）
6. 性能问题（N+1 查询、缺失索引、不必要的重渲染）
7. 类型安全缺口（any 类型、缺失验证）

对于每个：文件/行号、问题是什么、风险（低/中/高）、建议修复。

按风险排序，最高的在前。

Why it works: risk-based prioritisation helps you focus on what matters. You can deal with the high-risk items immediately while deferring the low-risk clean-up.

7. The code consolidator: keep the codebase DRY

Duplicated code is a maintenance nightmare. This two-part prompt helps you consolidate duplicates and remove dead code.

When to use: when you notice similar code in several places, or during a refactoring sprint.

Prompt:

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我有需要整合的重复代码。

1. 找到所有实例。列出它们。
2. 每个之间有什么不同？这些差异重要吗？
3. 创建一个处理所有情况的共享工具。灵活但不复杂。
4. 迁移计划：每个文件的前后对比
5. 风险评估：什么可能会出问题？

逐步进行。一次一个模式。

同时查找并删除死代码。

寻找：
1. 未使用的导出（已导出但从未导入）
2. 注释掉的代码
3. 不可达代码（return 之后、不可能的条件）
4. package.json 中未使用的依赖
5. 孤立文件（没有被导入的地方）
6. 旧的功能标志（始终为 true/false）

对于每个：是什么、在哪里、如何确认未使用、安全删除吗？

不要删除动态导入的代码。标记这些供手动审查。

Why it works: the incremental approach prevents big-bang refactors that break everything. The warning "don't delete dynamically imported code" (不要删除动态导入的代码) prevents a common mistake.

Part 4: Security and deployment (prompts 8-9)

8. The security auditor: ship safely

Security vulnerabilities can destroy your product and your reputation. This prompt helps you find problems before you go to production.

When to use: before every production deployment, after adding authentication/authorisation, or when handling sensitive data.

Prompt:

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生产前安全审计。

检查：
1. 注入攻击：SQL 注入、命令注入、XSS
2. 认证：硬编码密钥、弱密码、缺失速率限制、不过期的会话
3. 授权：IDOR、缺失的认证检查、可绕过的角色检查
4. 数据暴露：日志中的敏感数据、向用户显示堆栈跟踪、PII 泄露
5. 配置：调试模式、宽松的 CORS、缺失的安全头

对于每个问题：严重性、文件/行号、如何利用、如何用代码修复。

要彻底。深度思考。

Why it works: the requirement "how to exploit it" (如何利用) forces the AI to think like an attacker, which helps surface real vulnerabilities rather than theoretical ones.

9. The pre-launch checklist: deploy with confidence

Deploying to production is nerve-wracking. This checklist makes sure you haven't missed anything critical.

When to use: before every production deployment, especially your first.

Prompt:

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部署到生产环境。运行上线前检查清单：

环境：
- 密钥在环境变量中（不是硬编码）？
- dev/prod 有不同配置？
- .env.example 存在吗？
- 调试模式关闭了吗？

安全：
- 敏感路由有认证吗？
- 公共端点有速率限制吗？
- 到处都有输入验证吗？
- 强制 HTTPS 了吗？
- 设置了安全头吗？

错误：
- 有全局错误处理器吗？
- 向用户显示友好错误吗？
- 错误有上下文记录吗？

数据库：
- 迁移是最新的吗？
- 查询列上有索引吗？
- 有连接池吗？

对于每个：✅ 良好、⚠️ 需要注意（修复什么）、或 ❌ 缺失（如何添加）。

Why it works: the traffic-light system (✅⚠️❌) makes it easy to see what needs immediate attention and what's already handled.

Part 5: Testing and design systems (prompts 10-11)

10. The critical path tester: test what matters

Not all code needs tests, but critical paths absolutely do. This prompt helps you identify and test the parts that matter.

When to use: before launching a feature that handles money, data or authentication.

Prompt:

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为关键路径生成测试。

关键 = 如果损坏，会损失金钱、丢失数据、锁定用户或导致安全问题。

测试：
1. 认证流程：
   - 注册有效 → 用户创建
   - 注册现有邮箱 → 错误
   - 登录正确 → 会话
   - 登录错误 → 拒绝，无信息泄露
   - 未认证访问受保护路由 → 重定向

2. 数据变更（创建/更新/删除）：
   - 正常路径
   - 无效数据被拒绝
   - 不能变更他人数据
   - 失败的变更 = 无部分状态

3. 支付（如适用）：
   - 正常路径
   - Webhook 成功
   - Webhook 失败
   - 没有付费就没有付费功能

使用【你的框架：Jest/Vitest/Playwright】。AAA 模式。测试行为而不是实现。独立测试。

生成实际的测试文件。

Why it works: focusing on "critical paths" prevents test bloat. The instruction "test behaviour, not implementation" (测试行为而不是实现) keeps the tests valuable even when implementation details change.

11. The design system extractor: consistency at scale

As a codebase grows, design inconsistencies multiply. This prompt helps you extract and standardise a design system.

When to use: when you notice design inconsistencies, before a redesign, or when growing the team.

Prompt:

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从这个代码库中提取设计系统。

查找并标准化：
1. 颜色：扫描 hex/rgb。分类（主色、次色、背景、文本、成功、错误）。创建 CSS 变量。
2. 排版：字体、大小、粗细。创建比例尺。
3. 间距：边距、内边距、间隙。创建一致的比例尺（4、8、16、24、32px）。
4. 组件：重复模式（按钮、卡片、输入）。创建基础 + 变体。
5. 阴影/边框：标准化为 2-3 个选项。

输出：
1. 设计令牌文件
2. 何时使用什么
3. 需要修复的不一致性
4. 迁移计划

要实用。我应该明天就能用。

Why it works: the instruction "be practical. I should be able to use it tomorrow" (要实用。我应该明天就能用) prevents over-engineering. You get a usable design system, not a theoretical one.

Part 6: Advanced technique (prompt 12)

12. The deep-thinking activator: deeper reasoning when you need it

Sometimes you need the AI to think harder. This simple addition can noticeably improve output quality.

When to use: for complex problems, security audits, architecture decisions, or when the initial response feels shallow.

Prompt:

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深度思考。

Why it works: this meta-prompt activates a deeper reasoning mode in many LLMs. Use it alongside the other prompts whenever you need more thorough analysis.

Putting it all together

These 12 prompts form a complete toolkit for vibe coding:

Planning phase: use prompts 1-3 to plan before coding
Build phase: use prompts 4-5 to manage scope and debug effectively
Maintenance phase: use prompts 6-7 to keep code quality high
Release phase: use prompts 8-9 to deploy safely
Scaling phase: use prompts 10-11 to test and systematise
Any phase: use prompt 12 whenever you need deeper thinking

Final advice

1. Customise the bracketed parts: replace 【你的想法】 (your idea), 【功能】 (feature) and 【框架】 (framework) with your specific context

2. Chain prompts: use several prompts in sequence for complex workflows

3. Iterate: if the first response isn't perfect, refine your prompt with more context

4. Save your variants: as you customise these prompts, keep the versions that work best for your workflow

The key to effective vibe coding isn't just having good prompts; it's understanding when and how to use them. Start with these 12, adapt them to your needs, and watch your productivity soar.

Happy vibe coding!

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These prompts are designed for AI coding assistants such as Cursor and GitHub Copilot, and other LLM-powered development tools.