VibeCoder Vault vs. Cursor AI Prompts
Cursor is a great AI code editor. But the quality of its output depends entirely on the quality of your prompts. VibeCoder Vault gives you 407+ production-ready templates that make Cursor dramatically better.
VibeCoder Vault complements Cursor — it does not replace it.
Paste VibeCoder Vault templates into Cursor Chat or Composer for dramatically better output. Cursor handles the IDE integration; Vault handles the prompt engineering.
See the Difference
Same task in Cursor. Dramatically different prompt quality.
Refactoring a React component
Select code → Cmd+K → "refactor this to use hooks"
You are a senior React engineer specializing in performance optimization. Refactor this component: - Component: [PASTE CODE] - Current issues: [prop drilling / re-renders / mixed concerns] - Target patterns: custom hooks, React.memo, useCallback where needed Requirements: 1. Extract business logic into a custom hook 2. Memoize expensive computations 3. Split into presentational + container if over 150 lines 4. Add TypeScript strict types for all props 5. Preserve existing test contracts
Writing an API endpoint
Cmd+K → "create a POST endpoint for user registration"
You are a backend security engineer building production APIs. Create a POST /api/users/register endpoint: - Framework: [Next.js API route / Express / Fastify] - Database: [PostgreSQL via Prisma / Drizzle] - Auth: [bcrypt + JWT / Auth.js] Generate: 1. Input validation with Zod schema (email, password strength, username) 2. Rate limiting (5 attempts per IP per minute) 3. Password hashing with bcrypt (12 rounds) 4. Duplicate email check with timing-safe comparison 5. JWT token generation with appropriate expiry 6. Error responses following RFC 7807 Problem Details 7. Request logging (sanitized — no passwords in logs)
Debugging a performance issue
Select slow code → "why is this slow and how do I fix it?"
You are a performance optimization specialist. Diagnose and fix this performance bottleneck: - Code: [PASTE SLOW CODE] - Environment: [React / Node.js / database query] - Observed behavior: [page loads in 3s, should be <500ms] - Data scale: [~10K rows / ~1M records] Provide: 1. Root cause analysis with Big-O complexity 2. Profiling strategy (which metrics to measure) 3. Fix with before/after code 4. Performance benchmark expectations 5. Monitoring query to detect future regressions
How to Use Them Together
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Fill in [BRACKETS] with your specific code, framework, and requirements.
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