octomind aims to cut token waste in long agent runs
octomind is an agent that runs in the terminal. It focuses on a common problem in long agent sessions: they can become slower, less reliable, and more expensive as more information piles up. When many are connected, octomind does not keep every tool in the model’s context for the whole session.
It loads tools only when a task needs them, then uses LRU removal to drop tools that have gone cold, keeping the active tool list small. It also uses instead of endlessly adding more session history, so the model works from a shorter and more current context. Each run can have a hard cost cap, and the run stops when that cap is reached.
That prevents a retry loop from quietly spending more than planned. It also supports by role across providers, written as code, and MCP.
Key points
- It is an agent for terminal use.
- It loads MCP tools only when a task actually needs them.
- It uses LRU removal to keep unused tools out of the active context.
- It compacts context so do not keep growing without limit.
- It stops a run when the hard cost cap is reached.