Robust and Efficient Tool Orchestration via Layered Execution Structures with Reflective Correction
arXiv:2602.18968v1 Announce Type: new Abstract: Tool invocation is a core capability of agentic systems, yet failures often arise not from individual tool calls but from how multiple tools are organized and executed together. Existing approaches tightly couple tool execution with stepwise language reasoning or explicit planning, leading to brittle behavior and high execution overhead. To overcome these limitations, we revisit tool invocation from the perspective of tool orchestration. Our key insight is that effective orchestration does not require precise dependency graphs or fine-grained planning. Instead, a coarse-grained layer structure suffices to provide global guidance, while execution-time errors can be corrected locally. Specifically, we model tool orchestration as learning a layered execution structure that captures high-level tool dependencies, inducing layer-wise execution through context constraints. To handle execution-time failures, we introduce a schema-aware reflectiv
arXiv:2602.18968v1 Announce Type: new Abstract: Tool invocation is a core capability of agentic systems, yet failures often arise not from individual tool calls but from how multiple tools are organized and executed together. Existing approaches tightly couple tool execution with stepwise language reasoning or explicit planning, leading to brittle behavior and high execution overhead. To overcome these limitations, we revisit tool invocation from the perspective of tool orchestration. Our key insight is that effective orchestration does not require precise dependency graphs or fine-grained planning. Instead, a coarse-grained layer structure suffices to provide global guidance, while execution-time errors can be corrected locally. Specifically, we model tool orchestration as learning a layered execution structure that captures high-level tool dependencies, inducing layer-wise execution through context constraints. To handle execution-time failures, we introduce a schema-aware reflective correction mechanism that detects and repairs errors locally. This design confines errors to individual tool calls and avoids re-planning entire execution trajectories. This structured execution paradigm enables a lightweight and reusable orchestration component for agentic systems. Experimental results show that our approach achieves robust tool execution while reducing execution complexity and overhead. Code will be made publicly available.
Executive Summary
This article presents a novel approach to tool orchestration, focusing on efficient and robust execution of multiple tools in agentic systems. The authors propose a layered execution structure that captures high-level tool dependencies and employs a reflective correction mechanism to handle execution-time failures. The design ensures that errors are confined to individual tool calls, avoiding re-planning of entire execution trajectories. Experimental results demonstrate the effectiveness of this approach in reducing execution complexity and overhead while achieving robust tool execution.
Key Points
- ▸ Tool invocation in agentic systems often fails due to the combination of multiple tools, rather than individual tool calls.
- ▸ Existing approaches tightly couple tool execution with stepwise language reasoning or explicit planning, leading to brittle behavior and high execution overhead.
- ▸ The authors propose a coarse-grained layer structure for tool orchestration, which provides global guidance without requiring precise dependency graphs or fine-grained planning.
- ▸ A schema-aware reflective correction mechanism is introduced to handle execution-time failures and repair errors locally.
Merits
Strength in Design
The article presents a well-structured and easy-to-follow design for tool orchestration, which is a significant improvement over existing approaches.
Robustness and Efficiency
The experimental results demonstrate the robustness and efficiency of the proposed approach, which reduces execution complexity and overhead while achieving robust tool execution.
Demerits
Limited Scope
The article focuses on tool orchestration in agentic systems and may not be directly applicable to other domains or systems.
Implementation Complexity
The introduction of a reflective correction mechanism may add complexity to the implementation of the proposed approach.
Expert Commentary
The article presents a significant contribution to the field of tool orchestration, which is a critical component of agentic systems. The proposed approach is well-designed, efficient, and robust, and its implications are far-reaching. However, the article's focus on agentic systems may limit its direct applicability to other domains. Furthermore, the introduction of a reflective correction mechanism may add complexity to the implementation of the proposed approach. Nevertheless, the article's findings and recommendations have the potential to significantly impact the development of artificial intelligence and machine learning systems.
Recommendations
- ✓ Future research should explore the application of the proposed approach to other domains and systems, as well as the development of more robust and efficient implementation mechanisms.
- ✓ The article's findings should be taken into account in the development and deployment of artificial intelligence and machine learning systems.