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aeoess

agent-passport-system-mcp

by aeoess

create_reserve_attestation

Generate a signed reserve attestation to prove a delegation holds sufficient funds, enabling trusted agent commerce.

Instructions

Create a signed reserve attestation proving a delegation has actual funds (GPT #15).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYes
currencyNoUSD
office_idNo
ttl_secondsNo
delegation_idYes
charter_anchorNo
assurance_classYes
attestation_basisYes
attester_public_keyYes
attester_private_keyYes
false_attestation_penaltyNoreputation_slash
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds only that the attestation is 'signed' and 'proving actual funds,' but omits critical traits such as side effects, idempotency, security requirements (e.g., handling of private keys), or whether it verifies funds before attesting. The description is too sparse to provide meaningful transparency.

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

Conciseness4/5

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

The description is a single sentence of about 12 words, making it very concise. It front-loads the action and purpose. However, the parenthetical '(GPT #15)' is noise that does not aid an AI agent and could be removed, so it is not a perfect 5.

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

Completeness1/5

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

The tool is complex: 11 parameters, 3 enums, no output schema, and no annotations. The description provides only a high-level purpose and none of the operational context needed to invoke it correctly. It lacks return value information, error conditions, and any guidance on how parameters interact. This is critically incomplete.

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

Parameters2/5

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

The schema has 0% description coverage, and the description does not compensate. It mentions 'delegation' and 'funds' but does not explain any of the 11 parameters, such as assurance_class, attestation_basis, or the key fields. The enums are left entirely unexplained, leaving the agent to guess semantics. Some domain context is provided, but it is far from sufficient for correct parameter selection.

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

Purpose4/5

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

The description clearly states the verb and object: 'Create a signed reserve attestation' with the purpose 'proving a delegation has actual funds.' This distinguishes it from many sibling attestation tools, though it does not explicitly name alternatives. The parenthetical '(GPT #15)' is a minor distraction but does not obscure the core purpose.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like create_derivation_receipt or aps_create_attribution_receipt. There is no mention of prerequisites, common use cases, or exclusions. The tool appears to be an attestation-creation operation, but the description does not help the agent decide when this specific tool is the right choice.

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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