Developer releases open-source tool to catch AI agent breakage after model updates
A developer has released an open-source Python library called toolcontract to detect when AI model updates silently change an agent's tool-calling behavior. The library works by pinning a set of expected tool calls as a contract and re-running them against the live model to check for structural differences. Unlike evaluation frameworks such as promptfoo or DeepEval, toolcontract focuses narrowly on whether a tool call's structure, arguments, and trajectory remain identical after a provider ships a new model version. It supports OpenAI, Anthropic, and LiteLLM-compatible models, and integrates with pytest or a standalone CLI. The project is available on PyPI and GitHub under an MIT license at version 0.1.
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