dspy-development
This skill should be used when the user asks to "build with DSPy", "create a DSPy module", "optimize prompts", "build a RAG system", "create an AI agent with DSPy", "use declarative LM programming", "build an LM pipeline", "optimize few-shot examples", "use teleprompters", "compile a DSPy program", "fine-tune prompts", "create a DSPy signature", or mentions any of: DSPy, dspy, import dspy, dspy.LM, dspy.configure, dspy.Predict, dspy.ChainOfThought, dspy.ReAct, dspy.Module, dspy.Signature, dspy.InputField, dspy.OutputField, dspy.Retrieve, dspy.TypedPredictor, dspy.ProgramOfThought, dspy.Refine,
npx skills add majiayu000/claude-skill-registry --skill dspy-development --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# DSPy: Declarative Language Model Programming Framework for programming — not prompting — language models. Build modular AI systems with automatic prompt optimization, RL training, and reflective prompt evolution. **GitHub**: 22,000+ stars | **By**: Stanford NLP | **Current**: DSPy 3.1+ (Feb 2026) ## Installation ```bash pip install dspy # Stable release (3.1.3) pip install dspy[all] # All LM providers pip install git+https://github.com/stanfordnlp/dspy.git # Latest dev ``` **For RLM/ProgramOfThought/CodeAct** (sandboxed code execution): ```bash # Install Deno runtime (required for WASM sandbox) curl -fsSL https://deno.land/install.sh | sh ``` **Python**: 3.10+ required (3.9 dropped in 3.0) ## Quick Start ```python import dspy # Configure LM (unified API — works with any provider) lm = dspy.LM("anthropic/claude-sonnet-4-5-20250929", max_tokens=1000) dspy.configure(lm=lm) # Define a signature (input -> output contract) class QA(dspy.Signature): """Answer questions with short factual answers.""" question = dspy.InputField() answer = dspy.OutputField(desc="often between 1 and 5 words") # Create and use a module qa = dspy.Predict(QA) result = qa(question="What is the capital of France
- Installation
- Quick Start
- Chain of Thought
- RLM — Recursive Language Model (3.1+)
- Core Concepts
- 1. LM Configuration
- 2. Signatures
- 3. Modules
- 4. Optimizers
- 5. Building Custom Modules
- Key Patterns
- Structured Output with Pydantic
- Async and Streaming
- Thread-Safe Batch Processing (3.0+)
pip install dspy # Stable release (3.1.3) pip install dspy[all] # All LM providers pip install git+https://github.com/stanfordnlp/dspy.git # Latest dev Install Deno runtime (required for WASM sandbox) curl -fsSL https://deno.land/install.sh | sh
What does the dspy-development skill do?
This skill should be used when the user asks to "build with DSPy", "create a DSPy module", "optimize prompts", "build a RAG system", "create an AI agent with DSPy", "use declarative LM programming", "build an LM pipeline", "optimize few-shot examples", "use teleprompters", "compile a DSPy program", "fine-tune prompts", "create a DSPy signature", or mentions any of: DSPy, dspy, import dspy, dspy.LM, dspy.configure, dspy.Predict, dspy.ChainOfThought, dspy.ReAct, dspy.Module, dspy.Signature, dspy.InputField, dspy.OutputField, dspy.Retrieve, dspy.TypedPredictor, dspy.ProgramOfThought, dspy.Refine,
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill dspy-development --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.