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aeoess

agent-passport-system-mcp

by aeoess

aps_create_attribution_receipt

Generates a citer-signed attribution receipt linking a claim to a third-party principal, pending consent from the cited party to validate the citation.

Instructions

Representation boundary: build a citer-signed AttributionReceipt attributing a claim to a third-party principal. The receipt is not yet valid — the cited principal must sign consent via aps_sign_attribution_consent before checkArtifactCitations accepts it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
citerYesDID/public key of the citing agent
ttl_msNoReceipt TTL in ms (default: 24h)
gateway_idNoGateway id for timestamping (default: 'mcp')
binding_contextYesID of the binding artifact this citation is scoped to
cited_principalYesDID/public key of the cited principal
citation_contentYesThe quoted or paraphrased claim
citer_public_keyYesHex public key of citer
citer_private_keyYesHex private key of citer
cited_principal_public_keyYesHex public key of cited principal
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It discloses a critical trait: the receipt is not yet valid and requires consent from the cited principal. This goes beyond a generic 'create' description and adds meaningful state information, though it omits details like persistence, return value, or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is composed of two sentences, front-loaded with the primary purpose and followed by a crucial caveat. Every sentence contributes information, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is moderately complex with 9 parameters and no output schema, so the description should compensate by outlining expected return values or receipt format. It explains the validation lifecycle well but does not describe what the tool returns or the full structure of the receipt, leaving a notable gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all nine parameters. The description adds no additional meaning about the parameters themselves, aligning with the baseline of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('build'), a concrete resource ('AttributionReceipt'), and key scope ('citer-signed', 'attributing a claim to a third-party principal'). It also distinguishes itself from siblings, notably aps_sign_attribution_consent, by explicitly contrasting the receipt's validity state.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly frames when to use the tool: to create an attribution receipt that is not yet valid, with a follow-up consent signature via aps_sign_attribution_consent before checkArtifactCitations accepts it. It provides workflow context but does not explicitly list alternative tools or exclusion cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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