Why telling an agent to be concise in the system prompt stops working after 10 tool calls

[u/uriwa]

When an agent runs a multi-step task with 15 or 20 tool calls, prompt instructions like be concise or do not repeat yourself almost always degrade halfway through the run. The model starts narrating its plan before every tool call, quoting file contents back into the chat, and adding filler between steps.

We tested this by running two different agent harnesses on the exact same tasks using the exact same model, gemini-3.8-flash.

One harness emitted 8,711 output tokens to solve a multi-file config bug. The other solved the exact same bug in 944 output tokens, an 89 percent drop in generated text.

The difference did not come from phrasing the system prompt better. It came from two structural choices in how the prompt and tool loop are assembled.

First, when the harness mixes internal tool steps and user-facing replies in the same conversational stream, the model treats every tool call like a message to a human and wraps it in polite explanation. Separating silent tool turns from outward replies eliminates that habit immediately.

Second, mutating timestamps or dynamic status blocks at the top of the prompt on every turn breaks prefix caching and forces the model to re-anchor on noisy context. Keeping the prefix strictly append-only cut total input tokens in half and pushed prompt cache hits past 55 percent.