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Found 49 Skills
Interactive model selection workflow with paginated navigation. Use when users want to select a model interactively - guides them through provider selection then model selection using the question tool with pagination support for large lists.
Control image generation requests before execution. Use this when the user wants text-to-image, image edit, reference-image generation, product image, persona image, banner, thumbnail, storyboard image, or image batch variants and the skill must identify inputs, classify the task, choose model/reference rules, then hand off to image-batch-runner.
Process textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence, and file input handling.
Send assistance requests to an assistant, applicable to task scenarios such as Chinese cultural understanding, classical Chinese text comprehension, creation of Chinese characteristic works, writing promotion copy for Xiaohongshu and Douyin, writing test cases, information retrieval, etc. It is also a strong substitute and assistant for other expert assistants, and can be used as an alternative backup solution for most tasks.
Create and configure Claude Code sub-agents with custom prompts, tools, and models
Design cross-border logistics strategies including direct mail, overseas warehousing, and bonded warehouse models for international e-commerce. Use this skill when the user needs to ship products internationally, choose a logistics model for cross-border sales, optimize shipping costs, or set up fulfillment in a foreign market — even if they say 'ship to Southeast Asia', 'overseas warehouse vs direct shipping', 'customs clearance', or 'reduce international shipping time'.
Expert in streamlining and enhancing the development of AI Agent Applications, including AI app / agent / workflow code generation, AI model comparison and recommendation, tracing setup, and evaluation planning / setup / execution.
Optimizing vector embeddings for RAG systems through model selection, chunking strategies, caching, and performance tuning. Use when building semantic search, RAG pipelines, or document retrieval systems that require cost-effective, high-quality embeddings.
Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification
Analyze token usage patterns and recommend cost optimizations with estimated savings
Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, and LLM-as-a-judge verification
Monetization strategy for iOS/macOS apps. Covers readiness assessment, pricing model selection, tier structuring, free trial strategy, and implementation guidance. Use when deciding what to charge, how to price, or planning monetization end-to-end.