Tokenbill profiles LLM agent execution traces to reveal token waterfalls, re-sent prefix waste, prompt-cache behavior, and cache-breaker patterns. It provides concrete recommendations for reducing costs and is implemented in pure Python stdlib with no API keys required for the core library. The tool is especially useful for developers building and optimizing autonomous AI agents.
tokenbill is an AI & ML product. It focuses on understanding and reducing unexpectedly high token costs and inefficiencies in LLM agent workflows. tokenbill is an open-source project aimed at developers. The project is open source (MIT). It runs on the command line.
tokenbill first shipped in 2026. Among its 4 catalogued features are token usage profiling, prompt cache simulation, and cache-breaker detection.
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