god-llm-sdk

To implement exponential backoff with jitter for LLM SDK streaming, enforce explicit SDK versions, timeout controls, and safe defaults to handle transient errors robustly during real-time AI workflows.

Prevent hallucinated API signatures in the Anthropic Claude SDK by enforcing verifiable method signatures and strict anti-hallucination patterns, ensuring all calls map to explicit, documented SDK versions.

The best way to manage token budgeting across OpenAI and AWS Bedrock is enforcing strict token counting controls and verifiable method signatures to ensure safe defaults across cross-provider workflows.

Yes, this approach supports building adapters, tools, and agents for LangChain, LlamaIndex, DSPy, and Ollama workflows by applying verifiable SDK patterns, robust error handling, and anti-hallucination techniques.

You need explicit SDK versions and timeout controls for production-grade LLM tools to enforce safe defaults, prevent API hallucinations, and ensure reliable error handling during exponential backoff retry strategies.