Part of Build with Claude Using Code and Guides
Engineering Blueprint
Safety checkedGenerate SQL from Natural Language
Techniques for translating natural language questions into SQL queries with self-improvement and RAG.
What problem does this solve?
Demonstrates how to generate correct SQL from plain English using prompting, self-improvement loops, and retrieval-augmented approaches. The guide covers syntax validation, semantic correctness checks, and evaluation against actual database results.
How does it work?
- Set up a database schema and sample queries. 2. Use Claude to generate SQL from natural language. 3. Test generated queries for syntax and semantic correctness. 4. Optionally use RAG to inject schema context or self-improvement loops to fix errors. Output: SQL queries validated against multiple dimensions (syntax, data correctness, row counts).
Included Skills
No skills in this group
What's required to run this?
Guide uses SQLite for examples. Evaluation tests cover syntax, semantic correctness, and row-level accuracy.
Key Features
Self-improvement loops
Automatically fix SQL errors by running queries and feeding back error messages to Claude
Schema-based RAG
Inject relevant database schema context into prompts for more accurate SQL generation
Multi-level evaluation
Validate queries on syntax, data correctness, and row counts separately
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