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In a world where relationships matter as much as individual resources, nthlink proposes a systematic way to surface and reason about n-degree connections. Traditional hyperlinks capture direct references, and graph databases expose immediate neighbors, but many real-world insights depend on chains of relationships: the collaborator of a collaborator who influenced a study, the supplier two steps up a manufacturing chain, or the indirect citation path that shaped a theory. nthlink addresses these needs by formalizing how links, their provenance, and trust metadata are recorded and evaluated across multiple hops. At its core, nthlink defines a link object enriched with attributes: source and target identifiers, provenance (who asserted the link and when), weight or confidence, context tags, and optional cryptographic signatures. Crucially, nthlink treats multi-hop paths as first-class entities. A path of length n can be described with aggregated metadata — cumulative confidence, dominant contexts, and lineage — allowing applications to query and rank indirect relationships without recomputing from raw edges each time. Applications span search, recommender systems, data governance, and scholarly discovery. Search engines can use nthlink to boost results that are contextually connected via trusted multi-hop paths. Knowledge graph platforms can index common n-degree traversals to answer complex queries faster. In enterprise settings, nthlink helps trace data lineage through ETL pipelines and supplier networks, making risk assessments more transparent. In academic contexts, it can reveal the chains of influence behind a citation or detect communities of thought spanning multiple fields. The benefits of adopting nthlink include improved expressiveness for relationship-centric queries, better provenance tracking, and enhanced trust metrics when multi-hop evidence is considered. By incorporating signatures and assertion metadata, nthlink supports verifiable assertions, which is essential in environments where authenticity matters. Challenges remain. Storing and indexing path-level metadata increases storage and computation overhead. Determining meaningful aggregation rules for confidence and context across heterogeneous sources requires careful design and domain-specific tuning. Privacy and access-control on derived multi-hop relationships must be managed to avoid leaking sensitive inferred associations. Looking ahead, nthlink can mature through standardization efforts and integration with decentralized identity and verifiable credential systems. Combining nthlink with content-addressable storage and lightweight consensus can enable cross-organizational sharing of trustworthy link graphs. As data ecosystems grow more interconnected, a practical, metadata-rich approach to n-degree linking can unlock deeper insights while preserving provenance and trust — exactly the promise that nthlink aims to deliver.