Structured Context
Context organized with clear hierarchy, roles, and boundaries — making it machine-parseable, not just human-readable. The architectural practice behind Context Clarity.
Structured Context goes beyond writing clearly — it means organizing context so that the model can navigate it programmatically. This includes using explicit sections (system instructions, user data, task requirements), clear delimiters, labeled roles, and consistent formatting. Unstructured context forces the model to infer what's an instruction vs. what's data vs. what's an example — a form of Interpretation Overhead that structured context eliminates entirely. The difference is between a model reading a well-organized document and a model reading a wall of unmarked text.
More in Context Quality
Context Debt
Accumulated ambiguity, redundancy, and disorder in a conversation or prompt.
Context Load
The total volume and complexity of context a model must process in a single call.
Prompt Bloat
Oversized, redundant context that forces unnecessary reasoning.
Context Clarity
A state where the prompt contains only what the model needs — no ambiguity, no redundancy, high signal. The opposite of Context Debt.
Signal Density
The ratio of useful information to total tokens in a prompt. High signal density = low reasoning tax.
Prompt Hygiene
The practice of keeping prompts clean, structured, and free of accumulated noise. Preventive maintenance against Context Debt.
Context Freshness
How current and relevant the context is to the task at hand. Stale context — old instructions, outdated facts — increases reasoning cost even when well-structured.