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AgentDebugX: An Open-Source Toolkit for Failure Observability, Attribution, and

BACKGROUND
1 SIGNALFIRST DETECTED 22 July 2026
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27 Mar
Rethinking Failure Attribution in Multi-Agent Systems: A Multi-Perspective Benchmark and Evaluation

arXiv:2603.25001v1 Announce Type: new Abstract: Failure attribution is essential for diagnosing and improving multi-agent systems (MAS), yet existing benchmarks and methods

REPORT · WHAT · ArXiv CS.AIOPEN STORY
1 Apr
AgentFixer: From Failure Detection to Fix Recommendations in LLM Agentic Systems

arXiv:2603.29848v1 Announce Type: new Abstract: We introduce a comprehensive validation framework for LLM-based agentic systems that provides systematic diagnosis and improvement

REPORT · WHAT · ArXiv CS.AIOPEN STORY
17 Sept
Collective Loss of Control in LLM Agent Systems: An Epidemic Account of Mutation, Contagion, and Recovery

arXiv:2609.18460v1 Announce Type: new Abstract: How does a multi-agent system evolve from a local deviation into collective loss of control? We propose an epidemic explanation

REPORT · WHEN · ArXiv CS.AIOPEN STORY
6 May
Evaluating Agentic AI in the Wild: Failure Modes, Drift Patterns, and a Production Evaluation Framework

arXiv:2605.01604v1 Announce Type: new Abstract: Existing evaluation frameworks for large language models -- including HELM, MT-Bench, AgentBench, and BIG-bench -- are designed for

REPORT · WHEN · ArXiv CS.AIOPEN STORY
11 Aug
TelemetrySuffBench: Is Agent Telemetry Sufficient for Failure-Origin Diagnosis?

arXiv:2608.07899v1 Announce Type: new Abstract: Agent systems increasingly expose execution traces, yet telemetry that reveals a failure may still be inadequate for identifying

REPORT · WHERE · ArXiv CS.AIOPEN STORY
24 Sept
Toolcompass: Guiding Tool Trialing, Not Suppressing It

arXiv:2609.25678v1 Announce Type: new Abstract: Large language model (LLM) agents must generalize from tools seen during training to unseen tools at deployment. A key challenge is

REPORT · WHAT · ArXiv CS.AIOPEN STORY
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