title: “Evaluation Architecture” description: “Machine-readable governance rule evaluation within the AIGO Framework.”
Evaluation Architecture
The AIGO Evaluation layer defines how governance rules are applied to structured inputs and how evaluation results are produced.Purpose
Evaluation provides a structured mechanism for determining whether defined governance conditions are satisfied and whether further governance action may be required.Evaluation flow
A simplified evaluation flow is: input → rule selection → condition evaluation → action determination → result Evaluation inputs may include information about: * AI systems * classifications * risks * controls * evidence * changes * governance statusEvaluation results
An evaluation may produce outcomes such as: * pass * fail * not applicable * review required * additional governance action required The exact result semantics are defined by the applicable evaluation specifications and schemas.Evaluation components
The repository contains separate specifications for: * rule evaluation * evaluation semantics * semantic validation * evaluation input * evaluation result * governance evaluation orchestrationMachine-readable source
The evaluation components are maintained under:rules/evaluation/
The primary rule evaluation engine specification is:
rules/evaluation/AIGO-Rule-Evaluation-Engine-Specification-v0.2.md
Relationship to rules
Rules define the governance logic. Evaluation provides the mechanism for applying that logic to governance inputs. Keeping these concerns separate allows rules to be defined independently from the execution and evaluation mechanisms.Validation
Evaluation outputs can be validated against defined schemas and semantic requirements. The repository includes dedicated evaluation validation tests and fixtures under:validation/10-evaluation-validation/
and:
validation/tests/fixtures/