# A T-API-Compliant ReAct Agentic Loop for Optical Networks: Generic vs. Domain-Specific Tool Abstractions

arXiv: https://arxiv.org/abs/2606.18000 · HTML: https://mlsanity.com/paper/2606.18000/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Agentic AI for wireless networks, one of 16 directions in LLM agents and tool use.
- Builds on 6 of its 23 references that are in the map.
- First posted on arXiv 16 Jun 2026.

## Placed in

- LLM agents and tool use / [Agentic AI for wireless networks](https://mlsanity.com/agents/agentic-ai-for-wireless-networks/)

## Builds on (most cited first, 6 of 6)

- [ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs](https://mlsanity.com/paper/2307.16789/) (2023)
- [First Field Trial of LLM-Powered AI Agent for Lifecycle Management of Autonomous Driving Optical Networks](https://mlsanity.com/paper/2409.14605/) (2024)
- [When Large Language Models Meet Optical Networks: Paving the Way for Automation](https://mlsanity.com/paper/2405.17441/) (2024)
- [Enhancing Large Language Models (LLMs) for Telecom using Dynamic Knowledge Graphs and Explainable Retrieval-Augmented Generation](https://mlsanity.com/paper/2602.17529/) (2026)
- [Role of Digital Twin in Optical Communication: Fault Management, Hardware Configuration, and Transmission Simulation](https://mlsanity.com/paper/2011.04877/) (2020)
- [Agentic AI for Scalable and Robust Optical Systems Control](https://mlsanity.com/paper/2602.20144/) (2026)

## Abstract (arXiv)

Optical networks need intent-driven, closed-loop agentic management, a key enabler for higher autonomy levels. We present the first T-API-compliant reasoning and act (ReAct) loop. We show that domain-specific composite tools achieve 90% oracle-validated correctness with threefold token savings compared to generic tools.