Automate DSPy module development with predictors, optimizers, adapters, and GEPA integration.
npx skills add https://github.com/Zpankz/mcp-skillset --skill dspy-code
Please help me install this Agent Skill. Skill: dspy-code Source: https://github.com/Zpankz/mcp-skillset/tree/main/dspy-code Command: npx skills add https://github.com/Zpankz/mcp-skillset --skill dspy-code
Specialized AI assistant for DSPy development with deep knowledge of predictors, optimizers, adapters, and GEPA integration. Provides session management, codebase indexing, and command-based workflows.
Scaffolds a new DSPy project and runs initial validation with one command.
High-intent search queries and answers about installing and using this skill.
To build DSPy modules without manual prompts, you can use a declarative AI assistant that automates predictor development, signature creation, and pipeline assembly. It shifts focus from prompt engineering to module programming.
Yes, you can automate DSPy project initialization and validation in one step. The command-based workflow scaffolds a new project structure and runs initial validation immediately to ensure correct setup.
Yes, this workflow supports GEPA integration for DSPy optimization. It applies a specialized assistant to configure predictors, optimizers, and adapters specifically for GEPA integration during module development.
The best way to manage large DSPy codebases is using session management and codebase indexing. This tracks development progress and enables fast discovery of predictors and pipelines across complex projects.
To optimize and export DSPy pipelines for production readiness, execute the structured command workflow. It guides you from initialization through optimization to final export with built-in validation and code generation.
You need RAG and typed outputs in DSPy development when building complex agent templates and pipelines. The assistant provides deep knowledge to structure these features correctly within your declarative modules.
az9713Initialize a project with dark code prevention directories, CLAUDE.md section, and baseline audit.
jaredcroxtonBuild declarative language model programs with signatures and teleprompters for RAG pipelines.
JhonHanderConstruct RAG pipelines with OpenAI embeddings and FAISS, Chroma, or Pinecone vector stores.
ThedouglerDevelop LLM applications, RAG systems, and agents with vector search and agent frameworks.
