Use case

condense.chat helps coding agents keep longer working sessions.

Use condense.chat when your coding agent burns context on long system prompts, file reads, tool traces, test output, and multi-turn session history. The goal is to keep more useful working context before the request reaches the upstream model.

What problem it solves

Long system prompts that repeat rules, repo style, and tool policy
Tool output and logs that consume working context quickly
File reads and retrieved code that are expensive to forward verbatim
Session collapse when an agent has to compact or discard context too aggressively

How it fits into an agent stack

The public integration path is a drop-in proxy. Teams point their OpenAI-compatible or Claude-compatible client at condense.chat, let condense.chat compress eligible content in-flight, and receive the model response back unchanged.

Why this matters for coding agents

Coding agents fail when context windows fill with the wrong material. condense.chat is positioned as a way to keep more signal from prompts, code reads, and tool traces without forcing a full application rewrite.