Every time your LLM agent calls a tool and reads the result, you're paying a tax. Not in dollars — in tokens, latency, and reliability (ok, dollars then). The tool's output gets serialized into text, tokenized into the context window, attended to by the model, and then re-serialized when the model decides what to do next. If the next step is another tool call, the cycle repeats. Data that never needed the model's judgement flows through the most expensive component in your system — twice. Thi...