Dspy
Skill Verified ActiveBuild complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
To empower developers to build complex AI systems more systematically and efficiently by leveraging DSPy's declarative programming paradigm and automatic optimization capabilities.
Features
- Declarative LM programming
- Automatic prompt optimization
- Modular RAG systems and agents
- Data-driven prompt improvement
- Systematic LM pipeline development
Use Cases
- Building complex AI systems with multiple components
- Developing maintainable and portable AI pipelines
- Improving model outputs systematically with optimizers
- Creating reliable RAG systems, agents, or classifiers
Non-Goals
- Manual prompt engineering without optimization
- Complex AI systems without modularity
- Simple, single-prompt LM calls requiring no systematic improvement
Execution
- info:Pinned dependenciesDependencies are listed in SKILL.md but not explicitly pinned with versions, and Python scripts lack shebangs and side-effect headers.
Installation
npx skills add davila7/claude-code-templatesRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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