Building LLM-Powered Applications with Claude

Claude API integration for building LLM-powered applications across Python, TypeScript, Java, Go, Ruby, C#, and PHP.

- Defaults to Claude Opus 4.6 with adaptive thinking and streaming; supports tool use, structured outputs, batches, and file uploads through a single /v1/messages endpoint

- Language detection automatically routes you to the correct SDK documentation; includes decision trees for choosing between single API calls, workflows with tool use, and agentic loops

- Tool runner (beta in most languages) handles automatic loop execution; manual loops available for fine-grained control over approval gates, logging, and conditional execution

- Agent SDK (Python and TypeScript only) provides built-in file, web, and terminal tools with permissions, MCP support, and safety guardrails; Claude API is the right choice for custom agent tools

Building LLM-Powered Applications with Claude

This skill helps you build LLM-powered applications with Claude. Choose the right surface based on your needs, detect the project language, then read the relevant language-specific documentation.

Before You Start

Scan the target file (or, if no target file, the prompt and project) for non-Anthropic provider markers - import openai, from openai, langchain_openai, OpenAI(, gpt-4, gpt-5, file names like agent-openai.py or *-generic.py, or any explicit instruction to keep the code provider-neutral. If you find any, stop and tell the user that this skill produces Claude/Anthropic SDK code; ask whether they want to switch the file to Claude or want a non-Claude implementation. Do not edit a non-Anthropic file with Anthropic SDK calls.

Output Requirement

When the user asks you to add, modify, or implement a Claude feature, your code must call Claude through one of:

- The official Anthropic SDK for the project's language (anthropic, @anthropic-ai/sdk, com.anthropic.*, etc.). This is the default whenever a supported SDK exists for the project.

- Raw HTTP (curl, requests, fetch, httpx, etc.) - only when the user explicitly asks for cURL/REST/raw HTTP, the project is a shell/cURL project, or the language has no official SDK.

Never mix the two - don't reach for requests/fetch in a Python or TypeScript project just because it feels lighter. Never fall back to OpenAI-compatible shims.

Never guess SDK usage. Function names, class names, namespaces, method signatures, and import paths must come from explicit documentation - either the {lang}/ files in this skill or the official SDK repositories or documentation links listed in shared/live-sources.md. If the binding you need is not explicitly documented in the skill files, WebFetch the relevant SDK repo from shared/live-sources.md before writing code. Do not infer Ruby/Java/Go/PHP/C# APIs from cURL shapes or from another language's SDK.