whitelabel-ordering

prepare_order

Resolve a natural-language food order (one or more items) to concrete menu items and return a summary plus a confirmation token. Does NOT place the order. Call place_order with the returned token to actually place it.

Input Schema

TableJSON Schema

Name	Required	Description
`date`	No	Delivery date-time as an ISO-8601 UTC instant, e.g. '2026-07-25T12:00:00Z'. Must be in the future. Defaults to 5 minutes from now (as soon as possible) — only pass this when the user asks for a specific time.
`items`	Yes	The item(s) to order — one or more lines, each with an item name, an optional quantity (default 1), an optional size, and optional extra ingredients by name.
`notes`	No	Optional notes for the vendor.
`cutlery`	No	Whether to ask the restaurant to include disposable cutlery. Only pass this when the user says either way; omit to leave it to the restaurant's default. Ignored (with a note) by vendors that do not offer it.
`clientId`	No	clientId of the restaurant, from a list_vendors result. Omit only when the server is configured for a single restaurant.
`vendorId`	No	vendorId of the restaurant, from a list_vendors result. Omit only when the server is configured for a single restaurant.
`bringTerminal`	No	Whether the courier should bring a card terminal so the order can be paid by card on delivery. Pass true when the user wants to pay by card, false for cash; omit when they do not say. Ignored (with a note) by vendors that cannot take card on delivery.
`deliveryAddress`	Yes	Delivery address text, e.g. 'Orlovica Pavla 26'.

TDQS

A4.5/5.0

Behavior4/5

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

With no annotations present, the description carries the burden of behavioral disclosure. It explicitly states the operation does not place the order, which signals this is a non-committal preparation step, and describes the return as summary + token. This is strong but not exhaustive—auth requirements and token validity are not mentioned.

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?

Two tight sentences with the core purpose and the critical non-side-effect front-loaded, followed by routing info. No filler.

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 tool with 8 parameters but a fully documented schema and no output schema, the description supplies the essential missing context: what the tool does, what it returns, and that it doesn't place the order. The only minor gap is auth requirements, but the overall description is complete enough for correct invocation.

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% and every parameter (items, deliveryAddress, date, notes, cutlery, clientId, vendorId, bringTerminal) is documented in the schema itself. The tool description adds no additional parameter-level meaning, so it sits at the baseline of 3.

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 action ('resolve ... to concrete menu items') with a clear resource (food order) and output (summary + confirmation token). Explicitly distinguishes itself from place_order by stating it does NOT place the order, so an agent can immediately tell them apart.

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?

Directs the agent to call place_order with the returned confirmation token when the user wants the order actually placed, and explicitly states this tool does not place orders. This is a clear exclusion and routing to the correct sibling.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All whitelabel-ordering tools Inspect

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TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct action and resource: order status vs. order staging vs. order placement, vendor discovery vs. menu retrieval, and login initiation vs. code submission. There is no overlap or ambiguity; even sequential tools like prepare_order and place_order are clearly separated by their purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with lowercase and underscores (e.g., check_order, list_vendors, prepare_order). Even the login and logout tools fit the pattern as single verbs, and there is no mixing of conventions.

Tool Count5/5

With 10 tools, the surface is well-scoped for a restaurant ordering domain. It covers discovery, menu browsing, account management, login flow, order staging, placement, and status checking without feeling bloated or too thin.

Completeness4/5

The core ordering lifecycle is covered end-to-end (vendor -> menu -> login -> prepare -> place -> check). The only noticeable gaps are the absence of an explicit address-saving tool (though referenced in the login description) and no order cancellation or update capability, though these may be out of scope for typical ordering workflows.

Resources

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