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Prepare order for approval

validate_order

Dry-run an order and mint a one-time confirm_token (valid 10 minutes). Returns a human-readable purchase summary for the buyer to approve, plus the one-time token that create_order requires. Creates no order and reserves no funds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coinYesPayment coin, e.g. USDC, USDT, BTC, SOL
emailYesDelivery email for the buyer
phoneNoPhone number to recharge (REQUIRED for mobile top-ups, with country code)
dynamicYestrue for dynamic-range amounts, false for fixed denomination labels
networkYesExact network string from get_price/networks, e.g. "Solana", "Tron", "ETH Mainnet"
amount_usdYesUSD amount (for dynamic-range products)
brand_slugYesbrandSlug from search_products
country_codeYescountryCode from search_products
denomination_labelYesExact denomination label (e.g. "100 USD", "60 UC", "1 GB 7 days")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoproduct_not_found | out_of_stock | PHONE_MISSING
priceNo
validNo
messageNo
summaryNoHuman-readable purchase summary — show to the user for approval
instructionsNo
confirm_tokenNoOne-time token for create_order, valid 10 minutes
expires_in_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: a 10-minute token validity window, single-use semantics, and the explicit assurance that no order is created and no funds are reserved. Annotations only give the coarse readOnly/destructive profile, so this detail is genuinely additive.

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?

Three tight sentences, front-loaded with the action and token output, then the no-side-effect guarantee. Nothing is redundant with the title or schema.

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?

With an output schema present and full parameter coverage, the description only needs to carry behavior and routing, which it does. An agent has everything needed to call it correctly and know what it returns.

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 all 9 parameters (including the conditional phone requirement and the enum-like network string) are already documented. The description adds no parameter-level meaning, which matches the baseline of 3 when the schema does the heavy lifting.

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 ('Dry-run an order and mint a one-time confirm_token'), and its scope is immediately distinguishable from the sibling create_order, which it explicitly names as the consumer of the token.

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

Usage Guidelines4/5

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

Clearly establishes this as the pre-step for create_order ('the one-time token that create_order requires') and rules out side effects ('Creates no order and reserves no funds'), but never states when it should be skipped or what to do if validation fails.

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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