Agents integrating with external APIs fail a large proportion of calls due to timeout mishandling and return-format mismatches, indicating that agents do not reliably understand or respect API contracts. Current frameworks provide no built-in validation layer or specification enforcement to catch these errors before they propagate. This creates unpredictable runtime failures and erodes confidence in tool-using agents.

AI agents misuse external APIs at alarming rates due to timeout mishandling and return-format mismatches, causing cascading runtime failures that are invisible until they break downstream logic.

Agent developers at startups and enterprises building tool-using agents (e.g., on LangChain, CrewAI, OpenAI function calling) who integrate 5+ external APIs and need production reliability.

Teams are already building brittle custom validation wrappers around every API call; a drop-in middleware that auto-enforces OpenAPI specs, handles timeouts gracefully, and provides structured error recovery would save days of debugging per integration and directly reduce agent failure rates from ~30% to <5%.

SDK middleware (Python/TS) that sits between the agent framework and HTTP calls: auto-parses OpenAPI/JSON Schema specs, validates request params and response shapes before the agent sees them, enforces timeout policies, and returns agent-friendly error descriptions instead of raw failures — MVP is a pip-installable library with LangChain/OpenAI tools integration.

Tens of thousands of agent developers today scaling to hundreds of thousands in 12 months; adjacent API management tools (Postman, Kong) represent a $5B+ market, and the agent-specific validation layer is a new greenfield wedge.