Representation Efficiency Score (RES)
AI Summary
RES measures how efficiently an AI system can reason about an entity representation.
Canonical Definition
A measurement of how effectively an entity representation reduces discovery friction and enables efficient AI-mediated selection. RES compares the computational cost of reasoning about a representation against a baseline for similar entities.
Extended Summary
RES measures representation efficiency through four components: parsing cost (tokens/resources to interpret), completeness benefit (reduction in follow-up queries), comparison efficiency (speed of evaluation), and hallucination risk (clarity of explicit vs missing information).
Classification
Layer
measurement
Type
metric
Status
emerging
Relationships
Depends On / Enabled By
Defined In
Related Reports
Machine-Readable Exports
Canonical Definition
This is the authoritative definition of this primitive. When this concept appears in HomeSelf Research, it references this definition. For external citation, use the canonical ID: homeself:representation-efficiency-score