dspy-advanced-module-composition
Use for composing DSPy modules with Ensemble, MultiChainComparison, ensemble voting, sequential pipelines, and multi-program workflows.
dspy-bootstrap-fewshot
Use for BootstrapFewShot, bootstrapped demonstrations, teacher-model demos, and low-data DSPy prompt optimization.
dspy-custom-module-design
Use for creating custom DSPy modules, extending dspy.Module, reusable components, stateful modules, serialization, and module testing.
dspy-debugging-observability
Use for debugging DSPy programs, inspect_history, tracing LLM calls, custom callbacks, observability, monitoring, and cost tracking.
dspy-evaluation-suite
Use for evaluating DSPy programs with Evaluate, answer_exact_match, SemanticF1, custom metrics, baselines, and program comparisons.
dspy-haystack-integration
Use for integrating DSPy with Haystack, optimizing Haystack prompts, improving retrieval pipelines, and extracting DSPy prompts.
dspy-miprov2-optimizer
Use for MIPROv2, Bayesian optimization, instruction and demo tuning, and high-performance DSPy program optimization.
dspy-optimize-anything
Use for GEPA optimize_anything on text artifacts such as code, prompts, agent architectures, configs, and non-DSPy optimization targets.
dspy-output-refinement-constraints
Use for dspy.Refine, dspy.BestOfN, output constraints, validation, reward functions, and iterative output refinement.
dspy-rag-pipeline
Use for RAG pipelines, retrieval augmented generation, ColBERTv2, context retrieval, multi-hop RAG, and grounded DSPy answers.
dspy-react-agent-builder
Use for ReAct agents, tool-calling agents, dspy.ReAct, multi-step reasoning and acting, and GEPA agent optimization.
skill-perfection
Use this skill when you need to QA audit and fix a plugin skill file. Provides a methodology for verifying skill content against official documentation, fixing issues in-place, and producing verification reports.
dspy-advanced-module-composition
This skill should be used when the user asks to "compose DSPy modules", "use Ensemble optimizer", "combine multiple programs", "use dspy.MultiChainComparison", mentions "ensemble voting", "module composition", "sequential pipelines", or needs to build complex multi-module DSPy programs with ensemble patterns or multi-chain comparison.
dspy-bootstrap-fewshot
This skill should be used when the user asks to "bootstrap few-shot examples", "generate demonstrations", "use BootstrapFewShot", "optimize with limited data", "create training demos automatically", mentions "teacher model for few-shot", "10-50 training examples", or wants automatic demonstration generation for a DSPy program without extensive compute.
dspy-custom-module-design
This skill should be used when the user asks to "create custom DSPy module", "design a DSPy module", "extend dspy.Module", "build reusable DSPy component", mentions "custom module patterns", "module serialization", "stateful modules", "module testing", or needs to design production-quality custom DSPy modules with proper architecture, state management, and testing.
dspy-debugging-observability
This skill should be used when the user asks to "debug DSPy programs", "trace LLM calls", "monitor production DSPy", "use MLflow with DSPy", mentions "inspect_history", "custom callbacks", "observability", "production monitoring", "cost tracking", or needs to debug, trace, and monitor DSPy applications in development and production.
dspy-evaluation-suite
This skill should be used when the user asks to "evaluate a DSPy program", "test my DSPy module", "measure performance", "create evaluation metrics", "use answer_exact_match or SemanticF1", mentions "Evaluate class", "comparing programs", "establishing baselines", or needs to systematically test and measure DSPy program quality with custom or built-in metrics.
dspy-finetune-bootstrap
This skill should be used when the user asks to "fine-tune a DSPy model", "distill a program into weights", "use BootstrapFinetune", "create a student model", "reduce inference costs with fine-tuning", mentions "model distillation", "teacher-student training", or wants to deploy a DSPy program as fine-tuned weights for production efficiency.
dspy-gepa-reflective
This skill should be used when the user asks to "optimize an agent with GEPA", "use reflective optimization", "optimize ReAct agents", "provide feedback metrics", mentions "GEPA optimizer", "LLM reflection", "execution trajectories", "agentic systems optimization", or needs to optimize complex multi-step agents using textual feedback on execution traces.
dspy-haystack-integration
This skill should be used when the user asks to "integrate DSPy with Haystack", "optimize Haystack prompts using DSPy", "use DSPy to improve Haystack pipeline", mentions "Haystack pipeline optimization", "combining DSPy and Haystack", "extract DSPy prompt for Haystack", or wants to use DSPy's optimization capabilities to automatically improve prompts in existing Haystack pipelines.
dspy-miprov2-optimizer
This skill should be used when the user asks to "optimize a DSPy program", "use MIPROv2", "tune instructions and demos", "get best DSPy performance", "run Bayesian optimization", mentions "state-of-the-art DSPy optimizer", "joint instruction tuning", or needs maximum performance from a DSPy program with substantial training data (200+ examples).
dspy-optimize-anything
Universal text artifact optimizer using GEPA's optimize_anything API for code, prompts, agent architectures, configs, and more
dspy-output-refinement-constraints
This skill should be used when the user asks to "refine DSPy outputs", "enforce constraints", "use dspy.Refine", "select best output", "use dspy.BestOfN", mentions "output validation", "constraint checking", "multi-attempt generation", "reward function", or needs to improve output quality through iterative refinement or best-of-N selection with custom constraints.
dspy-rag-pipeline
This skill should be used when the user asks to "build a RAG pipeline", "create retrieval augmented generation", "use ColBERTv2 in DSPy", "set up a retriever in DSPy", mentions "RAG with DSPy", "context retrieval", "multi-hop RAG", or needs to build a DSPy system that retrieves external knowledge to answer questions with grounded, factual responses.
dspy-react-agent-builder
This skill should be used when the user asks to "create a ReAct agent", "build an agent with tools", "implement tool-calling agent", "use dspy.ReAct", mentions "agent with tools", "reasoning and acting", "multi-step agent", "agent optimization with GEPA", or needs to build production agents that use tools to solve complex tasks.
dspy-signature-designer
This skill should be used when the user asks to "create a DSPy signature", "define inputs and outputs", "design a signature", "use InputField or OutputField", "add type hints to DSPy", mentions "signature class", "type-safe DSPy", "Pydantic models in DSPy", or needs to define what a DSPy module should do with structured inputs and outputs.
dspy-simba-optimizer
This skill should be used when the user asks to "optimize with SIMBA", "use Bayesian optimization", "optimize agents with custom feedback", mentions "SIMBA optimizer", "mini-batch optimization", "statistical optimization", "lightweight optimizer", or needs an alternative to MIPROv2/GEPA for programs with rich feedback signals.
dspy-reasoning-modules
Use for DSPy reasoning modules including RLM, ProgramOfThought, CodeAct, Parallel, sandboxed execution, and long-context workflows.
dspy-signature-designer
Use for DSPy signatures, InputField, OutputField, typed inputs and outputs, signature classes, and Pydantic-style structured schemas.
dspy-simba-optimizer
Use for SIMBA optimization, mini-batch introspective optimization, self-reflective rules, stochastic ascent, and numeric-metric optimization.
dspy-gepa-reflective
Use for GEPA reflective optimization, ReAct agent optimization, feedback metrics, LLM reflection, and execution trajectories.
dspy-mcp-tool-integration
Use for MCP tools with DSPy, Model Context Protocol servers, dspy.Tool.from_mcp_tool, and ReAct agents over MCP-compatible tools.
dspy-optimizer-selection
Use to choose or compare DSPy optimizers including LabeledFewShot, BootstrapFewShot, MIPROv2, SIMBA, GEPA, BootstrapFinetune, Ensemble, and BetterTogether.
dspy-production-deployment
Use for deploying DSPy with save/load, configure_cache, restrict_pickle, track_usage, async execution, streaming, and production runtime controls.
dspy-adapters-multimodal
Use for DSPy adapter selection, JSONAdapter, XMLAdapter, ChatAdapter, native function calling, structured outputs, and multimodal inputs like dspy.Image or dspy.Audio.
dspy-better-together
Use for BetterTogether, prompt plus weight optimization, fine-tuning sequences, and strategy chains like p -> w -> p.
dspy-embedding-retrieval
Use for DSPy retrieval with dspy.Embedder, dspy.Embeddings, FAISS indexes, semantic search, and local or hosted embedding models.
dspy-finetune-bootstrap
Use for BootstrapFinetune, fine-tuning DSPy models, teacher-student distillation, weight optimization, and lower-cost deployment.