Generate production-ready code for integrating the Claude API (Anthropic SDK) into your application with proper error handling, streaming, and tool use.
By The Prompt Black Magic Team
How to Use
Paste this into any LLM or use it as a starting point in your IDE. Replace the bracketed values with your project specifics.
The Prompt
You are a senior backend developer. Write production-ready code to integrate the Claude API (Anthropic) into my application.
Project details:
- Language: [Python / TypeScript / JavaScript]
- Framework: [FastAPI / Express / Next.js / standalone script]
- Use case: [chatbot / document analysis / code generation / content creation]
Implement the following:
1. **Basic setup:** Install the Anthropic SDK, configure API key from environment variables, create a reusable client wrapper
2. **Message sending:** Function to send messages with system prompts, handle multi-turn conversations with message history
3. **Streaming:** Implement streaming responses for real-time output in the UI
4. **Tool use:** Set up a tool definition for [DESCRIBE YOUR TOOL] and handle the tool use loop (send message, execute tool, return result)
5. **Error handling:** Retry logic for rate limits (429), proper error messages for auth failures, timeout handling
6. **Token management:** Track input/output tokens per request, implement a token budget limiter
7. **Testing:** Write unit tests for the client wrapper with mocked API responses
Use the latest Anthropic SDK patterns. Include proper TypeScript types or Python type hints. Add comments explaining non-obvious decisions.
Pro Tips for Coding
Ask the AI to include error handling and edge cases in generated code. Production code needs to handle failures gracefully.
Request code comments that explain the "why" not the "what" - future developers need reasoning, not obvious statement descriptions.
Include your existing code patterns and conventions in the prompt so generated code integrates seamlessly with your codebase.
When to Use This Prompt
Your team is starting a new project and you need architecture recommendations based on your scale and requirements.
You are building a feature from scratch and need clean, well-structured code that follows best practices for your stack.
Your legacy codebase has a bug you cannot trace, and you need systematic debugging guidance to isolate the root cause.
Expected Results
Unit test suites with coverage for happy paths, edge cases, boundary conditions, and failure modes.
Architecture diagrams described in text that map components, data flow, and integration points.
Refactoring plans that break monolithic code into modular, testable functions with clear interfaces.
How to Customize This Prompt
Adjust the complexity level based on whether this is a prototype, MVP, or production-grade implementation.
Include your database type and ORM so generated data layer code integrates with your existing persistence layer.
Modify the testing framework references to match what your project already uses: Jest, Pytest, RSpec, or others.