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Found 916 Skills
Expert prompt optimization for LLMs and AI systems. Use when building AI features, improving agent performance, crafting system prompts, or optimizing LLM interactions. Masters prompt patterns and techniques.
Use to run day-to-day loyalty reward catalog management and fulfillment.
Core technical documentation writing principles for voice, tone, structure, and LLM-friendly patterns. Use when writing or reviewing any documentation.
LLM fine-tuning with LoRA, QLoRA, and instruction tuning for domain adaptation.
Use this skill when working with Apple's Foundation Models framework for on-device AI and LLM capabilities in iOS/macOS apps
Audit LLM token cost estimates against actual API usage. Activate on 'cost verification', 'token estimate accuracy', 'API cost audit', 'estimation variance'. NOT for pricing lookups, budget planning, or cost optimization strategies.
AI-led stakeholder interviews using LLMREI research-backed patterns. Conducts structured interviews to elicit requirements through context-adaptive questioning, active listening, and systematic requirement extraction.
Comprehensive patterns for building AI-powered code generation tools, code assistants, automated refactoring, code review, and structured output generation using LLMs with function calling and tool use. Use when "code generation, AI code assistant, function calling, structured output, code review AI, automated refactoring, tool use, code completion, agent code, " mentioned.
Model Context Protocol expert for building MCP servers, tools, resources, and client integrationsUse when "mcp server, model context protocol, claude code extension, building ai tools, tool definition, mcp transport, stdio transport, sse transport, resource provider, prompt template, mcp, model-context-protocol, claude-code, ai-tools, llm-integration, anthropic, server, protocol" mentioned.
Hugging Face Transformers best practices including model loading, tokenization, fine-tuning workflows, and inference optimization. Use when working with transformer models, fine-tuning LLMs, implementing NLP tasks, or optimizing transformer inference.
Guide for building MCP (Model Context Protocol) servers that integrate external APIs/services with LLMs. Covers Python (FastMCP) and TypeScript (MCP SDK) implementations.
Expert in building comprehensive AI systems, integrating LLMs, RAG architectures, and autonomous agents into production applications. Use when building AI-powered features, implementing LLM integrations, designing RAG pipelines, or deploying AI systems.