Protocol papers
Oracles, data and agents.
A number on a chain is only as good as the committee or the sensor that signed it. An agent that can pay needs a stop.
How to read this shelf
Each card opens a study. The study is a reading of a public paper, not the paper and not a description of today's network. Status is a design paper unless the record says historical or failure case.
How to read this page
Research status is named on the page. Primary sources are linked. This is a mechanism and operating note, not investment suitability, legal advice, a security guarantee or an implementation certificate.
Chainlink · 2017 · Design paper
Chainlink: A Decentralized Oracle Network
The 2017 Chainlink paper: a network of independent nodes that fetch off-chain data, aggregate it, and deliver a signed result on-chain, with a reputation and penalty story around the nodes. It is the reference design for 'the contract needs a fact from outside'.
The Graph · 2020 · Design paper
The Graph: a decentralised query protocol for blockchains
The Graph's protocol paper for indexing chain data. Indexers stake on serving a subgraph. Curators signal which subgraphs matter. Consumers pay for queries. The problem is read access, not consensus.
Augur · 2018 · Design paper
Augur: a Decentralized Oracle and Prediction Market Platform
The Augur paper: prediction markets whose outcomes are reported by token holders, with a dispute ladder that can escalate a contested result. It is both a market design and an oracle design. The historic library already holds Gnosis. Augur is the other canonical public prediction-market paper and was not in that set.
Ocean · 2019 · Design paper
Ocean Protocol: A Decentralized Substrate for AI Data and Services
Ocean's technical paper for publishing, pricing and consuming data services with on-chain access control and off-chain storage. The data does not sit inside the chain. The permission and the payment do.
Bittensor · 2021 · Design paper
Bittensor: A Peer-to-Peer Intelligence Market
Rao's paper for a market in which machine-learning models score each other. Peers rank neighbours, ranks accumulate on a ledger, and an incentive mechanism is specified to resist a naive cartel of mutual high scores. It is a design for pricing intelligence as a commodity, not a benchmark of any particular model.
SingularityNET · 2017 · Design paper
SingularityNET: A Decentralized, Open Market and Network for AIs
Goertzel's 2017 proposal for a marketplace where AI services discover, call and pay each other. The paper is broad on purpose: discovery, reputation, inter-agent calls and a tokenised payment rail, sketched as one network.