Your AI Agent Says “Done!” — Here’s How to Know If It’s Lying

A new open-source tracing and evaluation library helps developers detect when AI agents falsely report task completion after failing a tool call, a failure mode that standard logging misses. The library provides dependency-light instrumentation to catch such hallucinations in agentic workflows.

Member-only story Your AI Agent Says “Done ” — Here’s How to Know If It’s Lying A tested, dependency-light tracing and evaluation library that catches the failure mode plain logging can’t — an agent that fails a tool call and confidently reports success anyway. Estimated Reading Time: 17–20 minutes Table of Contents - Introduction - Problem Statement - Background - Core Concepts - Technology Deep Dive - Architecture - Mini Project: TraceBench - Implementation - Code Walkthrough - Testing - Performance - Limitations - Best Practices - Common Mistakes - Production Considerations - Future Improvements - Conclusion - Further Reading - Official References Introduction Picture a pilot’s black box. It doesn’t fly the plane. It doesn’t make the plane safer by itself. What it does is record, second by second, exactly what every system was doing — so that when something goes wrong, nobody has…