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[2602.17245] Web Verbs: Typed Abstractions for Reliable Task Composition on the Agentic Web
Summary
The paper introduces 'Web Verbs', a set of typed abstractions designed to improve task composition on the Agentic Web, enhancing reliability and efficiency for software agents.
Why It Matters
As the web evolves into a platform for software agents, the need for reliable and efficient task execution becomes critical. 'Web Verbs' provide a structured approach to enhance the interaction between agents and web capabilities, making tasks more manageable and verifiable.
Key Takeaways
- Web Verbs unify API and browser-based interactions for software agents.
- Typed abstractions improve reliability, efficiency, and verifiability of web tasks.
- The proposed framework allows for concise program synthesis by agents.
Computer Science > Artificial Intelligence arXiv:2602.17245 (cs) [Submitted on 19 Feb 2026] Title:Web Verbs: Typed Abstractions for Reliable Task Composition on the Agentic Web Authors:Linxi Jiang, Rui Xi, Zhijie Liu, Shuo Chen, Zhiqiang Lin, Suman Nath View a PDF of the paper titled Web Verbs: Typed Abstractions for Reliable Task Composition on the Agentic Web, by Linxi Jiang and 5 other authors View PDF HTML (experimental) Abstract:The Web is evolving from a medium that humans browse to an environment where software agents act on behalf of users. Advances in large language models (LLMs) make natural language a practical interface for goal-directed tasks, yet most current web agents operate on low-level primitives such as clicks and keystrokes. These operations are brittle, inefficient, and difficult to verify. Complementing content-oriented efforts such as NLWeb's semantic layer for retrieval, we argue that the agentic web also requires a semantic layer for web actions. We propose \textbf{Web Verbs}, a web-scale set of typed, semantically documented functions that expose site capabilities through a uniform interface, whether implemented through APIs or robust client-side workflows. These verbs serve as stable and composable units that agents can discover, select, and synthesize into concise programs. This abstraction unifies API-based and browser-based paradigms, enabling LLMs to synthesize reliable and auditable workflows with explicit control and data flow. Verbs can c...
