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by com.mart402
OverviewDiscussionsAdmin

Verify Invoice

verify_invoice
Idempotent

Verify extracted invoice fields: arithmetic consistency, line-item totals, JP registration number check-digit + corporate-number existence observation (official Japan NTA registry), accounting-ready JSON. $0.015/call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYesExtracted invoice fields: total_jpy, tax_jpy, reg_no, invoice_no, issue_date, due_date, vendor, customer
x_paymentNoOptional: base64 X-PAYMENT header value (x402 exact scheme, USDC on Base mainnet). Omit it to receive the payment requirements (accepts[] + docs) for this call without being charged.
line_itemsNoOptional line items [{description, amount_jpy}] to reconcile against the subtotal

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / fields / description
      Added value: +"Extracted invoice fields: total_jpy, tax_jpy, reg_no, invoice_no, issue_date, due_date, vendor, customer"
    • addedInput schema / properties / line_items / description
      Added value: +"Optional line items [{description, amount_jpy}] to reconcile against the subtotal"
  2. Changed1 schema field changed
    • addedInput schema / properties / x_payment
      Added value: +{
+  "description": "Optional: base64 X-PAYMENT header value (x402 exact scheme, USDC on Base mainnet). Omit it to receive the payment requirements (accepts[] + docs) for this call without being charged.",
+  "type": "string"
+}
  3. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate idempotent and non-destructive behavior, but the description adds meaningful details: it checks line-item totals, queries the official Japan NTA registry, and produces accounting-ready JSON. The explicit $0.015/call cost also sets accurate expectations about metering beyond what annotations convey.

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 two sentences, opens with the core action, and packs the key verification checks, output type, and cost without wasted words. Every clause earns its place.

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

Completeness4/5

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

There is no output schema, so 'accounting-ready JSON' is somewhat vague about the exact return shape. Still, the explicit sub-checks, the schema coverage, and the cost/payment note give an agent enough information to understand the call's behavior and expected result.

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 fields, x_payment, and line_items. The description's references to arithmetic consistency and line-item totals map loosely to those parameters but add no parameter-level syntax or format details beyond what the schema provides.

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 uses the specific verb 'Verify' and names the exact resource: extracted invoice fields. It lists concrete verification dimensions (arithmetic consistency, line-item totals, JP registration number check-digit, corporate-number existence via the NTA registry) and the accounting-ready JSON output, clearly distinguishing it from sibling extraction/parsing tools.

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

Usage Guidelines3/5

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

The description implies this tool is used after invoice extraction, when extracted fields need validation. However, it never names an alternative or states when not to use it, so an agent must infer the routing among the many sibling parse/extract/JP-tax tools.

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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