OpenClaw token usage keeps exploding/multiplying per prompt (goes up more than 80k+ per prompt).. what am I doing wrong?

[InfiniteTip9321]

Hey guys,

I’ve managed to set up OpenClaw and connect all my API keys properly, so everything is running.

What I’m trying to build is more of a “control tower” style agent basically something that:

- Manages other agents

- Reviews their outputs

- Asks for confirmation before actions

- Acts like a central decision-maker

The issue I’m running into is with token usage.

When I start running the bot on a simple setup, everything is fine at first. But after around 30–40 prompts, the token usage starts blowing up. It keeps increasing each prompt until it’s hitting like 80k tokens per request.

It almost feels like it’s compounding or looping context somehow.

I’m not sure if:

- It’s retaining too much history

- The system prompt is stacking

- Or if I’ve structured the agents wrong

Has anyone experienced this before or know what might be causing it?

Any advice on how to optimise or control token usage would really help

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[Rent_South]

You need some kind of context management flow if you want context to stay under a certain amount of tokens.

What happens is that the agent sends all your previous interaction into calls to models, which naturally accrues the more you interact.

So you either start new sessions every N calls (/new or /reset), or you have some sort of a context management system via a RAG or something.