What problem does it solve? Writing correct Claude API and Anthropic SDK code requires up-to-date knowledge of model IDs, SDK bindings across eight languages, beta headers, and features like prompt caching, adaptive thinking, compaction, and Managed Agents — details that change faster than model training data and are easy to get wrong. ## Core Features & Use Cases - Multi-language SDK guidance: Language detection routes to accurate code examples for Python, TypeScript, Java, Go, Ruby, C#, PHP, and cURL, with verified SDK signatures rather than guessed APIs. - Feature implementation: Covers streaming, tool use and tool runners, structured outputs, prompt caching, compaction, batch processing, Files API, and server-side tools with correct parameters and beta headers. - Model migration: Handles upgrades between Claude model versions (e.g., 4.6 to 4.8), retired-model replacements, and translation of deprecated patterns like budget_tokens and prefills. - Use Case: A developer asks to add prompt caching to an existing Python Anthropic SDK project; the skill detects the language, reads the caching reference, and produces code with correct cache_control breakpoints and usage verification. ## Quick Start Ask the assistant to add prompt caching to your Anthropic SDK project or to migrate your Claude API code to the latest model version.