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The Internet has evolved into a heterogeneous computational ecosystem comprising websites, web services, application programming interfaces (APIs), software applications, databases, artificial intelligence (AI) models, cloud platforms, and increasingly autonomous digital agents. These resources provide a wide range of computational, informational, and operational capabilities. However, their capabilities are generally described, exposed, discovered, and accessed through different technical mechanisms and platform-specific interfaces. Consequently, users and autonomous systems frequently need to identify individual services, understand their available functions, determine their compatibility with particular tasks, and coordinate multiple resources to accomplish intended outcomes. This fragmentation creates a fundamental challenge for the development of autonomous intent-driven computing: although the Internet contains numerous potentially useful capabilities, these capabilities are not necessarily represented within a unified, machine-interpretable discovery and assessment framework. This paper proposes Internet Capability Discovery and Representation (ICDR), a conceptual framework designed to support the systematic discovery, representation, assessment, and organization of heterogeneous capabilities available across the Internet. Rather than treating the Internet primarily as a collection of documents, websites, and independently operated applications, ICDR conceptualizes it as a distributed capability ecosystem in which computational resources expose identifiable functions that can potentially be discovered and coordinated according to user intentions. The central contribution of this framework is a unified Internet Capability Representation Model that describes heterogeneous digital resources through a common semantic structure while preserving their native interfaces and execution mechanisms. The proposed model incorporates capability identity, functional description, input and output specifications, operational constraints, interaction mechanisms, accessibility conditions, availability, reliability, security requirements, provenance, and compositional relationships. Building upon this representation, the framework introduces a capability discovery and assessment process comprising capability identification, description extraction, semantic normalization, capability indexing, intent-oriented matching, compatibility evaluation, availability verification, reliability assessment, and capability evolution management. A further contribution is the distinction between capability existence, discoverability, semantic suitability, technical compatibility, operational availability, invocability, and execution reliability. These dimensions are treated as related but independent properties, allowing an autonomous system to distinguish between a resource that theoretically provides a required function and one that can actually execute the intended operation under current conditions. The paper also introduces a capability composition perspective through which multiple heterogeneous Internet capabilities can be identified and organized into coordinated execution structures. This provides a conceptual foundation for connecting distributed websites, APIs, applications, AI models, databases, and external services within a common intent-driven computational environment. Importantly, ICDR is not proposed as a replacement for existing API specifications, service registries, semantic web technologies, tool-calling protocols, or web service discovery mechanisms. Instead, it seeks to establish a higher-level capability abstraction and coordination-oriented representation that can potentially operate across these heterogeneous technologies. The framework is intended to complement existing technical standards while addressing the broader problem of discovering and understanding the capabilities of the Internet as an integrated computational ecosystem. This paper develops the theoretical foundations, conceptual architecture, capability representation model, discovery mechanisms, assessment dimensions, composition principles, research propositions, evaluation methodology, and implementation considerations of ICDR. It presents a conceptual research framework and does not claim completed experimental validation or demonstrated performance superiority.
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Jincheng Zhang (2026) studied this question.
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