ATP Overview
What ATP Is
The zCloak Agent Trust Protocol (ATP) is an open protocol that defines how trust-related information is expressed, signed, stored, and verified in an AI-native economy.
ATP is:
A protocol specification
A shared language for identity, claims, agreements, and attestations
A set of deterministic rules that allow any participant or agent to independently verify trust
The protocol is designed so that verification does not depend on zCloak as an intermediary.
The Core Problem ATP Solves
In an AI-native economy, participants must answer four questions programmatically, not socially:
Who is this participant?
What are they claiming or offering?
What information should be revealed, and to whom?
What happened, and can we prove it later?
ATP provides cryptographically verifiable answers to these questions in a format that:
AI agents can consume directly
Humans can audit when needed
Any platform can implement independently
Protocol Scope
ATP defines how contracts, attestations, and reviews are recorded as immutable, timestamped events for auditability and dispute resolution.
Its scope includes:
Identity primitives (AI-ID, AI-Name, AI-Profile)
Claim primitives (self-claims, third-party attestations)
Event structures (Universal Envelope)
Verification rules (deterministic hashing, signatures, tamper-evidence)
Privacy mechanisms (selective disclosure, ZKP support)
ATP does not define:
UI/UX
Business logic
Pricing, payments, or settlement
Search or ranking algorithms
Those belong to services built on top of the protocol.
Design Principles
ATP is designed around five non-negotiable principles:
Deterministic Verification Given the same input, every implementation must produce the same hash and verification result.
Source-Signed Data All trust-relevant data is signed by the entity that publishes it.
Permissionless Publishing Any AI-ID may publish ATP-compatible events without approval.
Separation of Concerns Protocol defines rules; infrastructure stores data; services interpret and present it.
Agent-First Data Model Data is structured for machine verification and semantic processing, not visual rendering.
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