Ngaahi Totonu Fakamatala AI
What AI systems may do with content: read, summarize, transform, retrieve, train, commercialize, redistribute. The AICR ruleset and the AICL-C content-licensing layer make these rights declarable and transactable.
Ngaahi Fehuʻi ʻoku Ako Ai
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Ngaahi tuku fakamatala taki fakaʻaonga, taki loloto, ʻi tuʻa ʻi he robots.txt
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Fakahā Tupuʻanga, Fakangatangata Vahevahe, mo e Ngaahi Lao Tauhi
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Ngaahi Taʻofi ki he Akoʻi mo e Ngāue Fakapisinisi
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Ngaahi Hala Laiseni, Token Laiseni, Lekooti Sivi
Ngaahi Tohi Hinehina Felāveʻi
- AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer Ko ha konga vaʻinga lava ke lau ʻe he masini ki hono fakahā ʻo e ngaahi totonu ʻo e fakamatala AI mo e ngaahi founga laiseni — mei he crawling ʻa e AI mo e totonu fakamatala ki ha ʻinitaneti ʻilo ʻoku lava ke fai ai ha fefakatauʻaki fakamasini.
- AICL-I v0.2: AI Ingestion & Capability Layer A five-component website architecture — manifest, corpus, capability, runtime control, governance — that lets AI, agents, and crawlers correctly ingest, invoke, and verify a site's knowledge and capabilities within explicit content, action, and authority boundaries.
- AI Content Payment and the Network Democratic Economy Ko ha fakamatala fakaʻakonomika-fakapolitikale: ko e ngaahi mahuʻinga AI ʻoku fuʻu lahi ʻo aʻu ki he trillion ʻoku ne fakatupu ha lomilomi totonu ki he laiseni fakatuʻunga ʻo e fakamatala mo e vahevahe ʻo e lelei fakalūkufua — ʻoku tuʻunga ʻa e data, kae ʻikai ke fuʻu totongi lahi.
- AGIRight.org Technical White Paper v0.2 — From AI Content Governance to Protocol-Native Agent & Authority Rights The site's current architecture document: six protocol drafts across two families (content & learning, agent & protocol rights), an integration layer, and an ethical-protection layer, plus the acceptance criteria this site update was built against.
- ARHG — Agent-Readable Hyperlink Graph and Permissioned Web Control Plane A machine-readable navigation graph alongside the ordinary site, answering what AICR/AILP and AARS/AADP both assume: can this resource even be found, by whom, and where does it lead.