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MCP x402 - Evidence-Backed Web Verification

Preview an evidence-backed verification for free

preview_verification
Read-only

Use this free static preview before paying for verificar_condicoes. Choose offer_terms to inspect warranty, returns and availability; seller_trust to inspect seller identity and authorization; or policy_compliance to inspect required policy terms. It performs no web request, OpenAI call or payment and returns a realistic structured example plus the exact paid next step. PT: Pré-visualização gratuita e estática da verificação.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "preview_verification"
  }
}

Input Schema

NameRequiredDescriptionDefault
useCaseNoStatic example to return: offer_terms, seller_trust or policy_compliance. Defaults to offer_terms.

Output Schema

NameRequiredDescriptionDefault
kindYes
labelYes
priceYes
networkYes
useCaseYes
nextStepYes
paidToolYes
openAiUsedYes
exampleInputYes
paidEndpointYes
exampleOutputYes
paymentRequiredYes
preflightEndpointYes
liveRequestPerformedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

Goes beyond the readOnly/closed-world annotations by disclosing the crucial trait that output is a 'realistic structured example', not a real verification, and that no web request, OpenAI call or payment occurs. This prevents the main failure mode of an agent treating stub data as genuine evidence; only the 'exact paid next step' pointer is left vague.

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?

Front-loaded with the key routing instruction and the alternatives in one tightly packed sentence, followed by the no-side-effect guarantee. The trailing PT translation is boilerplate rather than substance, minor bloat.

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

Completeness5/5

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

For a single-parameter, no-side-effect preview tool with an output schema and full annotation coverage, nothing an agent needs to call it correctly is missing: cost, side effects, data fidelity, and the handoff to the paid tool are all covered.

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

Parameters4/5

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

Schema coverage is 100%, so the enum and default are already documented. The description still adds value by explaining what each enum value actually reveals (offer_terms inspects warranty/returns/availability, etc.), which the schema does not.

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?

States a specific verb and resource ('static preview' of the verification) and immediately distinguishes it from the paid sibling verificar_condicoes. An agent can tell exactly what this tool produces versus the real verification tool without opening either schema.

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

Usage Guidelines5/5

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

Explicitly says to use this free preview *before* paying for verificar_condicoes, then maps each useCase value to the content it inspects (warranty/returns/availability, seller identity/authorization, policy terms). Both the when-to-use and the selection logic are spelled out.

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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