Elad Baram enhanced the strands-agents/sdk-python repository by implementing robust context window overflow handling and token limit enforcement for LLM prompts. Using Python and leveraging backend development and exception handling skills, Elad introduced a user-facing overflow message that alerts users when prompts exceed the maximum token limit. He ensured reliability by adding comprehensive tests to verify that exceptions are raised in overflow scenarios, reducing the risk of silent failures. This work improved the predictability of LLM interactions and provided clearer guidance for token budgeting. The depth of the solution reflects careful attention to error messaging, testing, and overall system reliability.