Sample record. This work is fictional demonstration content. Results, people and institutions are placeholders; references in full-text articles are real publications.
Abstract
Agent developers inspect failed runs by hand, which does not scale beyond a few dozen trajectories. We propose a clustering approach that groups failures by the step at which the trajectory diverges from a successful reference run, and label the clusters with short natural-language descriptions. On 18,000 trajectories from three agent frameworks, the method recovers 83% of failure categories identified by manual analysis and surfaces four categories that were previously unreported.
Keywords agents · failure analysis · trajectories · clustering
Full text
CTM-PP-2026-0007-v1.pdf
Declarations
- Author contributions
- Author contributions are listed in the PDF.
- Funding
- Sample record – no funding to declare.
- Competing interests
- The authors declare no competing interests.
- Data and code availability
- Sample article. All results, names and affiliations in this demonstration article are synthetic placeholders.
Versions
Version 1 · 21 October 2026Latest
First version.
10.xxxx/ctm.pp.2026.0007.v1
How to cite
Rahman, A. & Hartwell, L. (2026). Mining Failure Modes from Agent Trajectories at Scale [Preprint, version 1]. CONTINUUM Preprints. doi:10.xxxx/ctm.pp.2026.0007
© 2026 The authors. Published by AEX CONTINUUM under the CC BY 4.0 licence.