Drizzle ORM Context Guide for AI Coding (llms.txt + Rules + MCP)
TypeScript ORM that feels like writing SQL. Zero-overhead, maximum type-safety, and lightning-fast query execution.
1. Drizzle ORM Official llms.txt & Clean Markdown Documentation
Official Support (Jeremy Howard Spec v2)Feed this clean, token-efficient Markdown documentation directly to Antigravity, Cursor, or Claude Code to prevent hallucinations and outdated API syntax.
# Standard llms.txt Index Endpoint
https://orm.drizzle.team/llms.txt
# Comprehensive Documentation Bundle
https://orm.drizzle.team/llms-full.txt
2. Production-Ready Drizzle ORM Cursor Rules (.cursorrules & .mdc)
Drizzle ORM schema declaration, relational queries, and migration practices. Save this into .cursor/rules/drizzle.mdc in your project repository.
// Drizzle ORM AI Rules
- Define schemas in separate schema/*.ts files and export through a central index.ts.
- Prefer Drizzle's relational queries (db.query) for nested JSON joins without manual aggregations.
- Run 'drizzle-kit generate' followed by 'drizzle-kit migrate' in deployment pipelines.
- Use prepared statements (db.select()...prepare()) for high-throughput API endpoints.
3. Drizzle ORM Antigravity & Claude Code System Instructions
Add this concise instruction block to your workspace .gemini/rules or project system prompt.
// Context Anchor for Drizzle ORM
When writing code for Drizzle ORM, refer directly to the verified specifications at https://orm.drizzle.team/llms.txt.
Follow strict error-handling and avoid deprecated API calls.
5. Troubleshooting: Common Drizzle ORM AI Coding Issues & Fixes
Frequently reported errors when LLMs generate Drizzle ORM code without proper context:
6. Best Used With (Drizzle ORM Architecture Combos)
Engineers building with Drizzle ORM frequently combine these complementary developer frameworks: