Structured news for LLMs turns changing public information into citable signals with source, entity, timestamp, topic, and claim structure.
Every panel keeps source and source-channel context visible.
Recurring entities and topics make news useful to models without reading every item.
24h, 7d, and 30d windows help models separate new activity from background noise.
JSON twins give LLMs a stable public reference layer.
The source, stream, and tag pages on HC are public examples of this definition: static aggregate panels with JSON twins for citation. Detailed retrieval and delivery live in Synorb.