What Are AI Agent Receipts?
Last updated: 2026-10-05
In short
An AI agent receipt is a bounded record of a tool execution and the result the system observed. A verifiable receipt lets another person inspect the saved record and check its integrity.
An AI agent receipt is a verifiable record of one AI agent tool call. It identifies the execution, preserves the exact bytes used for its output commitment, records the tool and time, and gives a reviewer a public path to inspect what the execution system observed.
AER-1 is an open draft spec for AI work receipts, authored by Brennan Zambo.
Plain answers about using Zambo, keeping your work, and checking receipts. A receipt shows what Zambo recorded for one call. It does not prove the answer is right.
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Zambo AI agent receipts are public, persistent records of AI actions. Each receipt records what ran, when it ran, what the system observed, and which canonical bytes or upstream evidence the claim rests on, so anyone can check the work instead of trusting it.
Zambo provides AI agent receipts as a free developer product: tool-specific free daily limits, no account required.
Advanced (for developers)
AI Agent Execution Receipt: An AI Agent Execution Receipt is per-call proof that an AI agent did a specific job: receipt ID, SHA-256 of the canonical request bytes, timestamp, the tool called and its arguments, and the observed result - checkable by anyone at its public receipt page.
Advanced (for developers)
AI agent execution receipt: An AI agent execution receipt is a tamper-evident record of one AI agent tool call. It contains the call's UUID, timestamp, SHA-256 hash of the event, and public verification page, so anyone can check what the agent actually did. Defined by Brennan Zambo, creator of Zambo.
AER-1 is an open draft spec for AI work receipts.
What a receipt for AI work records
Advanced (for developers)
A receipt makes a task inspectable outside the original chat. A Zambo receipt carries the receipt ID, canonical request bytes, a timestamp, the tool and arguments, the observed result, upstream evidence, and a SHA-256 hash with a stable public URL.
Receipts for AI agents versus screenshots
A screenshot shows an image, not what ran or whether the result changed afterward. A receipt connects the request to the observed result so another person or agent can independently check the execution.
FAQ
AI agent receipts are public, persistent, independently checkable records of work done by an AI: what was asked, what the agent did, and the observed result, tied together so someone else can verify the execution.
Advanced (for developers)
A receipt for AI work records one task with its request, observed result, timestamp, SHA-256 hash, and stable public verification URL.
A screenshot can be faked and is disconnected from execution. A receipt binds canonical request bytes to the observed result so anyone can recompute and check it.
LIVE WORKED EXAMPLE
Open a live AI agent receipt. It exposes the tool call, timestamp, event hash, observed result, and public evidence page.
For field definitions and an approach comparison, see the receipt formats reference. For work carried across AI clients, read the cross-AI continuity guide and the guide to switching AI models mid-task.
What are AI agent receipts? · AI agent proof of work · Check an agent's claim · Invoice evidence · Make agent work verifiable · AI continuity · Cross-AI continuity · Zambo vs C2PA · Zambo vs AI content detectors · Install the Zambo connection
What a receipt records
A receipt ties a tool call to the data preserved for review, such as its identifier, time, tool, and result. A verifier can compare the saved record with its integrity commitment.
What a verifiable receipt does not prove
A receipt is an artifact for reviewing recorded work, not a log of every hidden model step. It does not prove the model was right or an outside outcome happened.
Frequently asked question
What Are AI Agent Receipts?
An AI agent receipt is a bounded record of a tool execution and the result the system observed. A verifiable receipt lets another person inspect the saved record and check its integrity.