CAX-Agent: A Lightweight Agent Harness for Reliable APDL Automation
The paper introduces CAX-Agent, a lightweight agent harness designed for reliable automation in MAPDL finite-element simulations. It addresses challenges related to execution control and fault recovery by implementing a structured orchestration middleware. Empirical evaluations demonstrate that the model-driven recovery strategy significantly outperforms other methods in task completion and intervention rates.
- ▪CAX-Agent is built to enhance reliability in MAPDL automation by managing tool lifecycles and workflow states.
- ▪The architecture includes three layers: LLM service, agent harness, and solver backend, with a recovery ladder for escalating interventions.
- ▪Model-driven recovery achieved the highest completion rate of 92.67% and a strong inter-rater agreement score.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.15218 |
| Publication time | Mon, 18 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-18T04:04:54.418Z |
| Last seen | 2026-05-18T04:04:54.418Z |
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Computer Science > Artificial Intelligence arXiv:2605.15218 (cs) [Submitted on 12 May 2026] Title:CAX-Agent: A Lightweight Agent Harness for Reliable APDL Automation Authors:Chenying Lin, Yichen Hai, Yi He, Ran Wang, Haiyan Qiang, Liang Yu View a PDF of the paper titled CAX-Agent: A Lightweight Agent Harness for Reliable APDL Automation, by Chenying Lin and Yichen Hai and Yi He and Ran Wang and Haiyan Qiang and Liang Yu View PDF HTML (experimental) Abstract:Large language models deployed for MAPDL finite-element simulation face practical reliability challenges: without structured execution control, tool encapsulation, and fault recovery, outputs may be inconsistent and task failures are common.
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