AgriAgent: Contract-Driven Planning and Capability-Aware Tool Orchestration in Real-World Agriculture

• URL: http://arxiv.org/abs/2601.08308v1
• Date: Tue, 13 Jan 2026 07:53:09 GMT
• Title: AgriAgent: Contract-Driven Planning and Capability-Aware Tool Orchestration in Real-World Agriculture
• Authors: Bo Yang, Yu Zhang, Yunkui Chen, Lanfei Feng, Xiao Xu, Nueraili Aierken, Shijian Li,
• Abstract summary: AgriAgent is a two-level agent framework for real-world agriculture.<n>Simple tasks are handled through direct reasoning by modality-specific agents.<n>Complex tasks trigger a contract-driven planning mechanism that formulates tasks as capability requirements.
• Score: 10.079493887268507
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Intelligent agent systems in real-world agricultural scenarios must handle diverse tasks under multimodal inputs, ranging from lightweight information understanding to complex multi-step execution. However, most existing approaches rely on a unified execution paradigm, which struggles to accommodate large variations in task complexity and incomplete tool availability commonly observed in agricultural environments. To address this challenge, we propose AgriAgent, a two-level agent framework for real-world agriculture. AgriAgent adopts a hierarchical execution strategy based on task complexity: simple tasks are handled through direct reasoning by modality-specific agents, while complex tasks trigger a contract-driven planning mechanism that formulates tasks as capability requirements and performs capability-aware tool orchestration and dynamic tool generation, enabling multi-step and verifiable execution with failure recovery. Experimental results show that AgriAgent achieves higher execution success rates and robustness on complex tasks compared to existing tool-centric agent baselines that rely on unified execution paradigms. All code, data will be released at after our work be accepted to promote reproducible research.

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