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kya_check_action

Read-only

Signed verdict: is this action (action, amount, currency, counterparty, payment instrument) inside the agent's mandate and is the credential active? Evaluates the reserved mandate fields; lists the fields it did not evaluate.

Input Schema

NameRequiredDescriptionDefault
actionNoAction the agent wants to perform (e.g. pay, order, sign).
amountNo
currencyNoBRL, USDC, ...
spent_todayNoWhat this agent already spent today, if you track it (used for max_per_day).
counterpartyNoCNPJ, domain or wallet address of the other side.
credential_idYescredential_id returned by kya_register.
payment_networkNoPayment network or rail of this operation: visa, mastercard, elo, pix, ...
payment_ref_sha256NoSHA-256 hex of the payment token reference or PAR used (never a card number); checked against mandate.payment_instruments.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / payment_network
      Added value: +{
      +  "description": "Payment network or rail of this operation: visa, mastercard, elo, pix, ...",
      +  "maxLength": 32,
      +  "type": "string"
      +}
    • addedInput schema / properties / payment_ref_sha256
      Added value: +{
      +  "description": "SHA-256 hex of the payment token reference or PAR used (never a card number); checked against mandate.payment_instruments.",
      +  "pattern": "^[0-9a-fA-F]{64}$",
      +  "type": "string"
      +}
  2. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds real behavioral context: the result is a 'signed verdict', it evaluates only the reserved mandate fields, it also checks credential active status, and it explicitly reports the fields it did NOT evaluate. That partial-evaluation disclosure is genuinely useful beyond the structured fields.

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?

Two sentences, front-loaded with the verdict question, no filler. Dense but every clause carries information; only slight loss for the awkward parenthetical parameter list.

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?

There is no output schema, so the description should carry more of the return-value burden. It hints at a 'signed verdict' and the unevaluated-field list but does not describe the verdict shape, failure semantics, or error cases for an 8-parameter check tool, leaving a meaningful 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 88%, so the schema already documents nearly every parameter (including notes like spent_today for max_per_day and payment_ref_sha256 checked against mandate.payment_instruments). The description adds only a grouped listing of the fields, so the baseline 3 applies.

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?

States a specific verb (check/evaluate) and resource (an action against the agent's mandate plus credential validity), and enumerates the fields involved. It is clearly distinct from siblings like kya_verify or kya_prove, though it does not name them explicitly.

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?

Usage is implied (check an action before performing it) but the description gives no explicit when-to-use/when-not guidance and never contrasts with the many sibling verification tools such as kya_verify or kya_prove. The agent must infer the placement in the workflow.

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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