Dspy
技能 已验证 活跃Build 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.
功能
- Declarative LM programming
- Automatic prompt optimization
- Modular RAG systems and agents
- Data-driven prompt improvement
- Systematic LM pipeline development
使用场景
- 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
非目标
- 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.
安装
npx skills add davila7/claude-code-templates通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。
质量评分
已验证类似扩展
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