TokenTrim – context slimmer for coding agents

Cut coding agent token spend without losing output quality

Problem

A builder of coding agent tooling reports 90%+ API savings by using smaller context windows, client-side compaction, tool compaction, and system nudges. That's evidence many teams burn far more tokens than needed with coding agents and have no visibility into where the waste happens.

Solution

A local proxy layer that sits between the coding agent and the model: it compacts conversation history, trims redundant tool output, detects bloated system prompts, and reports token usage and cost per request. It doesn't change agent logic — just optimizes the pipe.

Users

Independent developers and small teams heavy on coding agents, AI tool builders

MVP

Local proxy intercepting requests; history and tool-output compaction; duplicate content detection; per-call token/cost comparison; one-toggle enable/disable

Revenue

Open-source core + $9/mo advanced dashboard; team tier with savings-share pricing

Why now

Coding agents are now daily workflow, token cost anxiety is real, and this optimization layer hasn't been absorbed by mainstream tools yet