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Syntelos: A Hierarchical Taxonomy of Intent in Digital Interactions

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Maintainer: Daniel Hardman · 2025-12-11 · checked 2026-10-15

A 2025 paper by Daniel Hardman proposing Syntelos, a hierarchical, machine-readable taxonomy of the intent (telos) of interactions, rooted in shared outcomes and drawing on Activity Theory and commitment protocols, for constraining delegation and negotiating interactions between human and AI agents. It surveys existing standards (industry and commodity codes, agent communication languages, Schema.org, privacy vocabularies, IEEE 7012) and proposes top-level categories such as /relate, /share, /trade and /govern.

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