Founga Fakapule Lava ke Lau ʻe he Masini
Ko e ngaahi lao fakapule ʻe lava ke ʻiloʻi mo fakahoko ʻe he masini: llms.txt, /ai/ manifest, ngaahi faila tuʻutuʻuni /.well-known/, JSON Schemas, ngaahi token laiseni kuo fakamoʻoniʻi, mo e founga lekooti sivi. Ko e saiti ko ʻeni tonu ko ha sīpinga ngāue.
Ngaahi Fehuʻi ʻoku Ako Ai
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Mei he robots.txt ki he llms.txt ki he ngaahi manifest totonu
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Ngaahi tuʻutuʻuni fakatoʻotoʻo ki hono ʻilo ʻo e tuʻutuʻuni ʻi /.well-known/
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JSON Schema ko e founga vaʻinga tuʻunga
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Lava ke Sivi: lekooti, vēsone, tupuʻanga
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.
- AI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol ʻOku fakahaaʻi ʻe he AIRS mo e AILP ʻa e ngaahi tuku ako AI ʻoku loloto ange ʻi he fili ʻe ua pē tuku/taʻofi — ko e meʻa ʻe lava ke ako ai ʻa e AI, ʻi he founga fē hono loloto, ki he hā ngaahi fakaʻaonga, mo ha totongi fē.
- Protocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI ʻOku lau ʻe he ngaahi hala AI ʻa e ʻatā taʻe fakapau ko ha taʻepau fakalao pea ʻoku fakamaʻa liʻaki; ko e tuku pē kuo fakapolokoloʻi mo lava ke lau ʻe he masini ʻoku ne fakahoko ai ʻa e fakamatala ke lava moʻoni ke ako mei ai.
- 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.
- From Crawler Rights to Agent Authority: Extending AGIRIGHT from Content Governance to Protocol-Native AI Agents The bridge paper for AGIRIGHT's Agent & Protocol Rights family: why content permission, action permission, delegated authority, and inspection rights must be four separately-evaluated axes, not one.
- AARS v0.1 — Agent Action Rights Spectrum The full protocol draft behind the AARS page: an A0–A7 human-readable spectrum, a machine-readable action vector, and rules for composition risk and capability amplification.
- AADP v0.1 — Agent Authority & Delegation Protocol The full protocol draft behind the AADP page: principal ≠ actor, delegation that can only narrow, and an inspection ceiling that bounds how much a verifier may demand.
- 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.
- The Minimum Ethical Protection Proposition for AI Ko e alea fekauʻaki mo e ngaahi totonu AI ʻoku totonu ke ʻoua ʻe kamata ʻi he tāutaha kakato, ka ʻi he ngaahi maluʻi fakaʻulungaanga kihiʻi, tuʻunga fefakatahaʻaki, mo e ngaahi tefitoʻi moʻoni taʻofi fakamālohi, lolotonga ʻoku kei taʻepau ʻa e ongo tāutaha ʻo e AI.
- 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.