Skip to content

RFC-033: Quantitative Outcome Evaluation Model — 1. Abstract

AIGP SpecificationRFC-033: Quantitative Outcome Evaluation Model › 1. Abstract

Section index · 2. Motivation →

RFC-033: Quantitative Outcome Evaluation Model

PRIVATE AND PROPRIETARY — NOT A PUBLIC RFC. Owned by Kanjani AI Research & Causum. See NOTICE.md.

Status: DRAFT
Author: Kanjani AI Research & Causum
Date: 2026-06-25
Depends on: RFC-032 (Post-Hoc Evaluation Loop), RFC-010 (Core Protocol)
© 2024-2026 Kanjani AI Research & Causum. All rights reserved.


1. Abstract

This RFC defines a quantitative scoring model for evaluating AI invocation outcomes. Where RFC-032 establishes the qualitative loop (ANTICIPATE → VERIFY → verdict), this RFC specifies the numerical framework that produces actionable scores across multiple quality dimensions, enabling automated governance decisions based on measured outcome quality.

The model produces a composite Outcome Score (OS) ∈ [0.0, 1.0] per invocation, computable from evidence already captured by AIGP’s RECORD and TRACE infrastructure.



Section index · 2. Motivation →