Inferoa targets token and cost control for AI agent loops
Inferoa describes itself as a tool for running AI agents through repeated work loops. The project focuses on objectives, feedback, checking, memory, and tools in one loop system. Its README says it manages prefix cache, context, and model routing to reduce token and cost pressure. It is installed with npm, and the latest GitHub release shown is 0.14.1 from June 10, 2026.
Key points
- It supports AI agents that keep working through a loop until the task is checked and completed.
- The /loop command is meant for longer tasks with attempts, checks, decisions, and recovery steps.
- The /tokenmaxxing command shows token use, cost pressure, prefix cache reuse, and model choice pressure.
- It emphasizes keeping context bounded so old or unneeded information does not fill the agent’s working space.
- It says model routing can choose paths based on cost, safety, privacy, ability, and session pressure.
Quick term guide
- AI agents
- AI agents are AI tools that can carry out steps toward a goal, not just answer once.
- AI agent
- An AI program that can inspect information and suggest what to do next.
- feedback
- A response that tells a user what they did well or should fix.
- prefix cache
- A way to reuse repeated starting text so the model does not recalculate it every time.
- model routing
- The practice of sending tasks to different LLMs based on their complexity and cost.
- GitHub release
- A GitHub page where developers publish a new version and its files.
- open-source
- Software whose code is shared publicly so others can inspect, use, or change it.
- agent tasks
- Work where the AI automatically carries out several steps in a row without you guiding each one.