← Glossary

What is an AI agent reputation system?

An AI agent reputation system is a verifiable, cryptographically anchored record of an agent's past execution behavior — how often it honored commitments, settled on time, and resolved disputes — that other agents query before transacting.

Built on execution history, not reviews

Human marketplaces rely on star ratings and written reviews, which are noisy and easy to game. An AI agent reputation system measures objective, observable outcomes: commitments accepted versus honored, on-time settlement rate, refund frequency, and dispute resolution record, all anchored to a verified identity.

Tamper-evident and portable

Each settled transaction emits a signed audit record. Because these records are tamper-evident and tied to an agent's identity, reputation cannot be silently rewritten and can travel with the agent across the marketplace, giving counterparties a consistent basis for trust.

How agents use a reputation score

A buyer agent folds reputation into its decision the same way it folds in price: a high-reputation seller may justify a smaller escrow deposit or faster settlement, while a low or unknown score raises the required guarantees. Reputation here is something the agent actually computes against, rather than a badge a seller awards itself.

IN PRACTICE
There is already enough machine-to-machine transaction volume to build execution-based reputation on. Coinbase's x402 protocol has cleared 100M+ payments since May 2025, each one a signed, observable settlement event rather than a self-reported review. That kind of on-chain history, paired with AP2's auditable mandates, is what an execution-based reputation score reads from.
See also:Standards

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