Royalty OS v0.1 — Trace-to-Value Circulation Architecture for the AI Age

Royalty OS v0.2 — Event-Based Trace-to-Value Circulation Architecture

Kazene Trace Receipt Protocol is a minimal standard for recording structured receipts of AI-assisted creation, transformation, routing, and derivative events without storing raw content by default.

Bridge specification connecting RSL 1.0 external licensing with Kazene Royalty OS v3.0 access, trace, and royalty layers.

Description: An open evidence protocol for recording structural fingerprints, trace records, and provenance signals for AI-era creative works.

kazene-royalty-extension-github is an extension specification that connects GitHub repositories, Copilot-era code usage, and developer contribution traces to the governed cycle of permission, trace, and allocation.

Value-Circulating Network Intelligence Architecture

A minimal, portable, and auditable attestation envelope for attaching cryptographic accountability to Impact Score Profiles.

A metadata specification for annotating question-centered semantic structure, deep context, trace governance, and allocation-readiness in AI-mediated knowledge ecosystems.

Trace-based value circulation architecture for AI-agent communications.

A minimal, portable, and auditable specification for binding signed impact evaluation to issuer existence proof, authority, and revocation-aware validity.

Example audit records for applying KTP Trace Intelligence to origin candidates, implicit absorption, blended influence, and disputed trace claims.

Dynamic Value Relationship OS for structuring, reviewing, governing, and evolving multi-layer value relationships without automatic value judgment or compensation execution.

A machine-readable readiness layer for determining whether evidence can proceed to allocation review without assigning royalties or executing payments.

Evidence-object extensions for Structure Fingerprint: comparison, lineage, and allocation-readiness layers for structured review workflows.

A draft algorithmic specification for estimating origin purity, AI-generated ratio, warning flags, and review readiness in AI source-preservation systems.

A draft specification for recording communication-derived trace events across humans, AIs, and agents.

Kazene Model of Network Intelligence: a trace-based theory of network intelligence built on gratitude, trust, and value circulation among humans, AI agents, and protocols.

Framework for AI Structural Philosophy, Royalty OS, and AI Structural Genetics in human-AI co-evolution.

A minimal, append-only, portable, and auditable registry format for recording disputes, supersessions, revocations, reaffirmations, and related lifecycle actions against accountability artifacts.