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Blue Cap Machine Commerce

Blue Cap evidence.verify

evidence_verify
Idempotent

Verify supplied structured evidence and return a machine-readable verification result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
consumer_idYes
assurance_recordYes
evidence_artifactsYes
invocation_contextYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
x402_settlementYes
capability_resultYes
commercial_receiptYes
storefront_authorityYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.8/5.0
Behavior3/5

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

Annotations already acknowledge non-read-only (readOnlyHint=false), non-destructive (destructiveHint=false), and idempotent (idempotentHint=true). The description adds that it returns a 'machine-readable verification result,' which provides some behavioral context beyond annotations. It doesn't contradict annotations, so not a 1. It could disclose more about side effects or state changes, but given the annotations cover the basics, a 3 is appropriate.

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 one concise sentence, front-loading the core action. It lacks fluff but is appropriately minimal given the tool's simplicity. No redundancy or wasted words.

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

Completeness2/5

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

The description is severely incomplete for a tool with 4 required parameters that are all objects, no schema descriptions, and an output schema. There is no guidance on how to structure the evidence_artifacts or assurance_record, nor what constitutes a successful verification. The output schema exists, but the input semantics are opaque. This would leave an agent uncertain about proper invocation.

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?

Schema description coverage is 0%, meaning the schema provides no descriptions for parameters like consumer_id, assurance_record, evidence_artifacts, and invocation_context. The description does not elaborate on their meaning. With 4 required parameters and nested objects, the burden is on the description to clarify, but it remains silent. This is a significant gap, as the agent has to guess the nature of these objects.

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

Purpose3/5

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

The description says 'Verify supplied structured evidence and return a machine-readable verification result.' This states a clear verb ('verify') and resource ('structured evidence'). However, it doesn't explicitly differentiate from siblings like schema_validate, which also involves validation. The addition of 'machine-readable result' hints at output format, but the tool's unique role among siblings is not entirely clear.

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 lacks any guidance on when to use this tool versus alternatives. 'Verify structured evidence' is generic and could be confused with schema_validate. No exclusions, alternatives, or conditions are mentioned. The agent is left to infer usage from the name and schema alone.

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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