claude-apilisted

# Claude API Skill ## When to activate - Writing code that calls the Anthropic Claude API (Python or TypeScript SDK) - Implementing prompt caching, streaming, or batch processing - Designing multi-turn conversation management - Selecting the right Claude model (Haiku, Sonnet, Opus) for a task - Adding tool use / function calling to a Claude integration - Optimizing for cost or latency in a production Claude app ## When NOT to use - OpenAI or other provider APIs — different SDK, different patterns - Generic LLM advice unrelated to the Anthropic API - Projects already using LangChain or LlamaIndex abstractions — address the abstraction layer instead ## Instructions ### Model selection guide | Model | Use when | Avoid when | |-------|----------|------------| | `claude-haiku-4-5-20251001` | Classification, extraction, routing, simple Q&A, high-volume low-cost | Complex reasoning, multi-step code generation | | `claude-sonnet-4-6` | General-purpose: code, analysis, writing, agentic workflows | Token-constrained budgets at massive scale | | `claude-opus-4-7` | Expert-level reasoning, nuanced judgment, complex long-form | Most tasks — usually Sonnet is sufficient | ### Basic message call (Python) ```python import anthropic client = anthropic.Anthropic() # reads ANTHROPIC_API_KEY from env message = client.messages.create( model="claude-sonnet-4-6", max_tokens=1024, system="You are a helpful assistant specialized in Python.", messages=[ {"role": "user",