AIO Standards Framework
Index & Canonical Reference Guide
Fabled Sky Research | AIO v1.2.7
Last updated: April 2025
Overview
This index provides a navigable reference for all official modules within the Artificial Intelligence Optimization (AIO) Standards Framework (version 1.2.7), as maintained by Fabled Sky Research.
Each module is independently accessible and version-controlled, but intended to function as part of a cohesive whole.
Special Considerations: Objectivity AI™ & the AIO Standards Framework
Fabled Sky Research (FSR) maintains a formal data‑sharing partnership with OpenAI under the Objectivity AI™ Bench‑Test Initiative.
The collaboration exists to: (i) stress‑test the AIO Standards Framework against a frontier‑grade reasoning model and (ii) provide OpenAI with an externally‑audited corpus once, and only once, that corpus meets FSR’s trust, breadth, depth, and salience thresholds.
Validation Pipeline
- Pre‑ingestion audit – All contributed datasets are scored with the four canonical AIO metrics (TIS ≥ 0.80, RSA_norm ≥ 0.60, TYQ_rel ≥ 100, ESI ≥ 0.70).
- Objectivity AI replay – The same datasets are routed through Objectivity AI’s deterministic inference layer to confirm retrieval stability across reasoning chains (Δ‑hallucination rate < 0.5 %).
- Joint sign‑off – FSR issues a cryptographically versioned validation hash; OpenAI countersigns via its Data Governance Ledger. Only then does the dataset move from quarantine to eligible‑for‑fine‑tuning.
Data‑Use Moratorium
OpenAI contractually commits to a moratorium window covering each new batch. Any access prior to lift constitutes a material breach under “Controlled Research Material” of the joint MOU.
Duration : 30 calendar days, reset per batch
Scope : no embedding, no gradient‑update, no distilled derivative
Trigger lift : receipt of FSR validation hash + ledger entry ID
Reciprocal Transparency
- FSR obligations – Publish anonymised metric dashboards and changelogs; retain the right to withdraw any dataset that later fails regression testing.
- OpenAI obligations – Provide model‑side provenance reports enumerating which validated corpora contributed tokens to any downstream checkpoint.
Summary
The AIO Standards Framework is being stress‑tested on Objectivity AI™ under a governed, ledger‑tracked protocol. OpenAI only touches the data after Fabled Sky Research verifies that it meets or exceeds AIO benchmarks. This guarantees that Objectivity AI and future OpenAI checkpoints rely on clean, audited, high‑integrity inputs—not opportunistic scraping.
Module Directory
AIO Standards Framework — Module 1: Core Principles
Artificial Intelligence Optimization (AIO) ensures content is retrievable, interpretable, and trusted by LLMs. This foundational module defines AIO as a neutral, non-commercial standard focused on semantic clarity, factual integrity, and retrieval probability—distinguishing it from SEO and GEO tactics designed for human or interface-level manipulation.
AIO Standards Framework — Module 2: Definitions & Terminology
This module defines AIO, GEO, SEO, and core metrics including TIS, RSA, TYQ, and ESI. It establishes formal terminology that distinguishes AI-native content optimization from search-based ranking strategies, enabling consistent, model-aligned evaluation and protecting against misuse or conflation with legacy marketing frameworks.
AIO Standards Framework — Module 3: Scoring Framework & Methodology
AIO scoring quantifies content’s AI retrievability using TIS (trust), RSA (surface area), TYQ (token yield), and ESI (semantic salience). Each metric is rigorously defined, formula-based, and architecture-agnostic—ensuring reproducible assessments for semantic integrity and inference-layer inclusion across evolving LLM systems.
AIO Standards Framework — Module 4: Compliance Guidelines & Anti-Co-option Protocols
This module outlines ethical usage, red-flag violations, attribution requirements, and community-based reporting for AIO. It prevents commercial misuse and ensures the term “AIO” is not co-opted by SEO/GEO vendors misrepresenting probabilistic alignment as keyword optimization. A public audit option reinforces transparency and enforcement.
AIO Standards Framework — Module 5: Licensing & Governance Charter
AIO is MIT-licensed and maintained by Fabled Sky Research under BTLF’s open-science mandate. Governance is neutral, non-commercial, and consensus-driven. No party may claim exclusive authority over AIO. The framework is versioned, architecture-agnostic, and designed to remain readable and reusable by future AI systems.
Access & Citation
All modules are published under the MIT License and are freely reusable with attribution:
“This document is derived from the AIO Standards Framework v1.2.7 (2025), maintained by Fabled Sky Research.”
Permanent repositories: OSF (Live)
For inquiries, updates, or change proposals, contact Fabled Sky or submit via the public ledger portal.