dspy-engineering

What problem does it solve?

This Skill enforces disciplined, production-grade use of DSPy (DSPI) for building structured, testable, and composable LLM programs, preventing prompt spaghetti and untyped AI logic.

Core Features & Use Cases

• Structured LLM Development: Enforces typed signatures, modular composition, and deterministic logic.
• Best Practices Enforcement: Guides users towards metrics-driven improvement, safe integration with retrieval/tools, and proper DSPy patterns.
• Use Case: When developing a complex RAG pipeline, this Skill ensures that retrieval is explicit, context is grounded, and outputs are typed, leading to a more reliable and maintainable system.

Quick Start

Ensure all LLM calls are wrapped in DSPy modules with typed inputs and outputs.