Luyalu lua Kutangwa kwa Masini
Nsiku mia luyalu bilenda monwa ye salakana kwa masini: llms.txt, ba-manifest za /ai/, minkanda mia politiki mia /.well-known/, ba-schema za JSON, tokeni za lisansi zasinama, ye maniela ma minkanda mia odite. Sité yayi kiawu kiawu i mbandu yisadilanga.
Kiuvu ki nyekolwa
01
Tuka robots.txt tii kwa llms.txt tii kwa minkanda mia minsua
02
Kifu kia lumonwa lua politiki muna /.well-known/
03
JSON Schema banga fomati ya spesifikasio ya nsiku
04
Kimalendila kia Fiongononwa: minkanda, vesio, ye nkulu
Minkanda mpembe ifwene
- AICR / AICL as an AI Content Licensing and Agentic Payment Connection Layer Kimvuka kia spesifikasio kia kutangwa kwa masini mu diambu dia kusakula minsua mia kontenu kia AI ye masalu ma lisansi — tuka mu kutambula kwa AI ye minsua mia kontenu, tii kwa web ya zayi ilenda salakana mombongo kwa masini.
- AI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol AIRS ye AILP keti monisa ndingisa za kulonguka kwa AI za mayindu ma nda vana ndambu ya “ee kaka voti ve kaka” — kina AI kilenda longuka, tii mu ntinu nki, mu diambu dia nki nsadulu, ye ntangu nki mfutu.
- Protocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI Kuzibuka kikondwa nsasilu keti tangwa banga lukatu lua nsiku kwa nzila za AI ye keti sukulwa; kaka ndingisa yina protokoliswa, ilenda tangwa kwa masini, keti vanga kontenu kilenda longukwa kikieleka.
- 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 Mvovo wa mbongo ya kimvuka: mbongo ya AI ya kimemo kia trillion keti vanga lukumu lua kimfunu mu diambu dia lisansi ya kontenu ya baniveo ye kikabu kia mbongo ya kimvuka kioso — mambu ma zayi meti kituka ma baniveo, ka ma ntalu yayingi kaka ko.
- 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 Disolo dia minsua mia AI difweti banda ka mu bumuntu bua mvimba ko, kansi mu lukebulu lua fioti lua moráli, nsiku mia soluka, ye minsiku mia vs-bimbi, ntangu kimonika kia bumuntu bua AI kikidi kilukatu.
- 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.