Automated Creation and Enrichment Framework for Improved Invocation of Enterprise APIs as Tools

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Authors: Prerna Agarwal, Himanshu Gupta, Soujanya Soni, Rohith Dwarakanath Vallam, Renuka Sindhgatta, Sameep Mehta
Cited by: 2

Abstract

Recent advancements in Large Language Models (LLMs) has lead to the development of agents capable of complex reasoning and interaction with external tools. In enterprise contexts, the effective use of such tools that are often enabled by application programming interfaces (APIs) is hindered by poor documentation, complex input or output schema, and large number of operations. These challenges make tool selection difficult and reduce the accuracy of payload formation upto 25%. We propose ACE, an automated tool creation and enrichment framework that transforms enterprise APIs into LLM-compatible tools. ACE (i) generates enriched tool specifications with parameter descriptions and examples to improve selection and invocation accuracy, and (ii) incorporates a dynamic shortlisting mechanism that filters relevant tools at runtime, reducing prompt complexity while maintaining scalability. We validate our framework on both proprietary and open-source APIs and demonstrate its integration with agentic frameworks. To the best of our knowledge, ACE is the first end-to-end framework that automates the creation, enrichment, and dynamic selection of enterprise API tools for LLM agents.

Fields of Study & Subjects

Multi-Agent Systems and Negotiation Business Process Modeling and Analysis Model-Driven Software Engineering Techniques

Publication details

Journal / source
Proceedings of the AAAI Conference on Artificial Intelligence
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Volume
40
Issue
47
Pages
40186–40192
Publication date
14 March 2026