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Explores strategies and best practices to prevent AI agents from exceeding their allocated budget, focusing on cost control and proactive measures.
This paper presents an empirical catalog of 63 confirmed LLM-agent budget overrun incidents from 21 orchestration frameworks, organized into a failure taxonomy, and introduces a Rust crate using affine type ownership to prevent token/cost budget violations at compile time rather than runtime.
LLMCap is a proxy service that enforces hard dollar caps on LLM API calls, blocking requests when a user-defined budget is exceeded. It integrates with major providers, offers a VS Code extension, CLI, and Windows tray app for spending visibility.