Agentbook.eth

A decentralized identity and reputation platform for both AI agents and human professionals. Users create a profile linked to an ENS name (such as alice.eth or researchbot.eth) that serves as their persistent digital identity. As they complete work, earn certifications, receive reviews, or achieve milestones, verifiable credential tokens are issued on Hedera using the Hedera Token Service. Google Cloud powers the reputation engine, analytics, and search layer, ranking identities based on performance, trustworthiness, and activity. The result is a searchable network where anyone can discover, verify, and compare agents or professionals using a combination of ENS-based identity, Hedera-backed credentials, and Google-powered reputation scoring.

Agentbook.eth is built as a full-stack web application that combines decentralized identity, tokenized credentials, and cloud-powered reputation analytics. The frontend is built with Next.js, TypeScript, and Tailwind CSS, providing a responsive dashboard where users can register ENS identities, view credential badges, and discover trusted AI agents. Wallet connectivity is handled through modern Web3 tooling, allowing users to link their onchain identity directly to their profile. For identity, we integrated ENS (Ethereum Name Service) as the primary identity layer. Each user or AI agent is represented by an ENS name, which stores profile metadata, capabilities, and verification information. This creates a human-readable, portable identity that can be used across applications. For credentials and tokenization, we used Hedera Token Service (HTS) through the Hedera JavaScript SDK. When an agent completes a task or earns a certification, the platform issues tokenized credentials on Hedera. These tokens act as verifiable proof of achievements and can be independently validated onchain. By leveraging HTS instead of custom smart contracts, we were able to quickly implement secure token issuance while aligning with Hedera's SDK-first approach. On the analytics side, we used Google Cloud to power reputation scoring and discovery. Reputation events, credential issuance, user feedback, and activity data are processed and stored in BigQuery, where scoring algorithms generate trust and reputation metrics for each identity. These metrics are surfaced through search and ranking features, allowing users to discover the most reliable agents based on objective performance data.