Agent Compass by Future AGI

Debugging Agents had been an issue for a while I love this tool a lot, helps me save so much time

Great tool

This is such a needed tool! Debugging agent failures has been a nightmare, and it’s awesome to see a solution that focuses on root-cause visibility instead of just surface-level errors.

A solid step forward for AI builders Agent Compass makes direction in agent workflows clear and effortless.

Hey Dev Hunt community! Nikhil here, Founder & CEO at Future AGI. Today, I’m really excited to share Agent Compass, something no other Agent monitoring or evaluation tool offers and we are the first one. Why did we build this? Over the past few months, I kept seeing the same problem across AI teams: debugging agents is chaotic. Teams would spend hours digging through logs and dashboards, trying to piece together why an agent failed. One small change in a prompt, a tool, or a data source could cascade into errors that nobody could fully trace. I’ve literally watched engineers spend days chasing failures, only to realize the root cause was something completely unexpected. And to make things worse, the current evaluation tools don’t really help. They just flag that something broke, without giving any clue about why or how to fix it. How does it actually work? Agent Compass is a zero-config evaluation tool for AI agents. It automatically identifies issues like hallucinations, traces their causes across prompts, tools, retrievals, and guardrails, and suggests fixes that teams can apply right away. Instead of looking at errors one by one, it shows patterns across your entire agent fleet, making debugging faster and more reliable. It builds a truth graph for your agents by linking errors across prompts, tools, and execution steps. It automatically clusters failures into a small set of root causes and generates an error tree that shows how one issue cascades across the workflow. Instead of drowning in fragmented traces and logs, you get a clear narrative of what broke, why it happened, and how to fix it. With zero-config evals, setup takes just a few lines of code. Debugging stops being a full-time job and starts becoming a fast, reliable process. Where we’re headed This is revolutionary. The vision is to make AI agents as reliable and predictable as traditional software, no matter how complex their workflows become. This will bring us closer to true autonomous reliability. Thanks for checking this out. I’d love to hear your thoughts, and how your team handles debugging multi-tool AI agents today! ▶️ Debug your AI agents in 5mins. - Try Agent Compass for free-> https://shorturl.at/yVWSb - Tech Docs -> https://shorturl.at/0ATkG - Research Paper -> https://shorturl.at/91n0w