dspy-ruby
SolidThis skill should be used when working with DSPy.rb, a Ruby framework for building type-safe, composable LLM applications. Use this when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers (OpenAI, Anthropic, Gemini, Ollama), building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.
Install
Quality Score: 81/100
Skill Content
Details
- Author
- davekilleen
- Repository
- davekilleen/Dex
- Created
- 6 months ago
- Last Updated
- today
- Language
- Python
- License
- NOASSERTION
Integrates with
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
core-code-intelligence-lsp
Engineering doctrine for using Language Server Protocol tools in agent code-analysis workflows for {{PROJECT_NAME}}. Covers per-language LSP server selection, diagnostic triage, type-query patterns, and the critical discipline of anchoring analysis to structured semantic data rather than string matching. Use when performing non-trivial code review, refactoring, type-safety analysis, or any task where grep alone cannot distinguish a definition from a reference or a type from its alias.
sota-llm-engineering
State-of-the-art LLM application engineering rules (mid-2026 baseline) for BUILDING and AUDITING LLM-powered features. Claude should use this skill whenever it is building, modifying, or reviewing anything that calls a language model — chat features, RAG pipelines, agents and tool use, structured extraction, classification, summarization, embeddings/vector search, evals and regression gates, prompt or context engineering, model selection/routing, fine-tuning decisions, or LLM cost/latency/observability work. Trigger keywords: LLM, AI feature, prompt, system prompt, context window, RAG, retrieval, embeddings, vector DB, rerank, chunking, agent, tool use, MCP, multi-agent, evals, golden set, LLM-as-judge, fine-tuning, model selection, routing, structured output, JSON schema, prompt caching, token budget, hallucination, grounding. Covers build-quality only — for prompt-injection/agent-security use sota-code-security rules/08 and sota-sandboxing rules/05.
using-ldd
Use at the start of any conversation, and whenever the user mentions LDD, loss-driven development, loss, gradient, SGD on code, drift, refinement loop, outer loop, inner loop, method evolution, or says "LDD:" / "apply LDD". Establishes how to dispatch the ten LDD skills and when each fires. Must be the first skill considered in any coding task where LDD is available.