Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing...
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Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing...
ai-personalization
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Building AI-powered personalization systems: recommendation engines, collaborative filtering, content-based filtering, user preference learning, cold-start solutions, and LLM-enhanced personalized...
document-ai
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Comprehensive patterns for AI-powered document understanding including PDF parsing, OCR, invoice/receipt extraction, table extraction, multimodal RAG with vision models, and structured data...
prompt-optimization
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Transform vague requests into production-ready, hallucination-free prompts optimized for Claude 4.x. Applies investigation-first protocols, anti-hallucination guards, extended thinking patterns,...
voice-ai-integration
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Build voice-enabled AI applications with speech recognition, text-to-speech, and voice-based interactions. Supports multiple voice providers and real-time processing. Use when creating voice...
ai-model-nodejs
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Use this skill when developing Node.js backend services or CloudBase cloud functions (Express/Koa/NestJS, serverless, backend APIs) that need AI capabilities. Features text generation...
pdd
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This sop guides you through the process of transforming a rough idea into a detailed design document with an implementation plan and todo list. It follows the Prompt-Driven Development methodology...
vibe-coding
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Turn an idea into a functional, demo-ready prototype using AI-assisted “vibe coding” (timeboxed build loop, prompt pack, build plan, demo script, and safety checks). Use for rapid prototyping and...
Clean code patterns for Azure AI Search Python SDK (azure-search-documents). Use when building search applications, creating/managing indexes, implementing agentic retrieval with knowledge bases,...
prompt-optimizer
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llm-game-development
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Comprehensive guide to using LLMs throughout the game development lifecycle - from design to implementation to testingUse when "ai game development, llm game dev, claude game, gpt game, ai coding...
Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with Pydantic validation.
Building production-ready Model Context Protocol servers that expose tools, resources, and prompts to AI assistantsUse when "mcp server, model context protocol, mcp tool, mcp resource, claude...
dspy
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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
ai-risk-mapper
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This skill should be used when identifying, analyzing, and mitigating security risks in Artificial Intelligence systems using the CoSAI (Coalition for Secure AI) Risk Map framework. Use when...
effect-ai-provider
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Configure and compose AI provider layers using @effect/ai packages. Covers Anthropic, OpenAI, OpenRouter, Google, and Amazon Bedrock providers with config management, model abstraction, and...
Generate and improve prompts using best practices for OpenAI GPT-5 and other LLMs. Apply advanced techniques like chain-of-thought, few-shot prompting, and progressive disclosure.
Generate and improve prompts using best practices for OpenAI GPT-5 and other LLMs. Apply advanced techniques like chain-of-thought, few-shot prompting, and progressive disclosure.
cloudflare
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Build and deploy on Cloudflare's edge platform. Use when creating Workers, Pages, D1 databases, R2 storage, AI inference, or KV storage. Triggers on Cloudflare, Workers, Cloudflare Pages, D1, R2,...