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Glama

create_order

Validate and place an order at a meni.ge location. Returns orderId (keep it — it is the access token for status checks) and the computed total. customer.name/phone are required for pickup and delivery; delivery.address is required for delivery. Pass either items (inline) or cartId (the cart built with update_cart) — not both. Always pass idempotencyKey when you might retry: the same key within 48h returns the original order instead of placing a second one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsNo
notesNo
cartIdNoOrder this cart; mutually exclusive with items
domainYes
pickupNo
qrCodeNo
customerNo
deliveryNo
languageNo
orderTypeNo
paymentMethodNo
idempotencyKeyNoRetry guard, e.g. a UUID you keep for this order attempt

TDQS

A4.8/5.0
Behavior5/5

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

No annotations are present, so the description carries full disclosure responsibility. It reveals that orderId serves as an access token for status checks, that idempotencyKey deduplicates within 48 hours, and the return includes computed total. This is rich behavioral context beyond the schema.

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 sentences, front-loaded with action, followed by return values, required-field conditions, and retry guidance. No fluff and every sentence contributes to successful invocation.

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?

Given 12 nested parameters, no output schema, and no annotations, the description provides essential information: returns, idempotency, and order-source options. It does not explain validation failure behavior or payment details, but the most critical usage contracts are 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 only 17%, so the description must add meaning. It clarifies mutual exclusivity of items/cartId, required customer fields, delivery address requirement, and idempotencyKey semantics. However, several parameters (orderType, paymentMethod, pickup.scheduledFor, qrCode) are only defined in the schema without description or narrative, so coverage remains partial.

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 clearly states the tool's function: validate and place an order at a meni.ge location. It specifies the resource (order) and differentiates from sibling tools like create_reservation or update_cart by focusing on order placement and providing return values.

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?

Provides explicit usage rules: pass either items or cartId (not both), customer.name/phone required for pickup/delivery, delivery.address for delivery, and idempotencyKey for retry scenarios. These are concrete when-to-use instructions that prevent misuse.

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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TDQS

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct resource/action: menu, item, search, cart, order, reservation, availability, store info, and policies. Even similar tools like get_item vs search_products are clearly differentiated by exact lookup vs semantic search. There is no meaningful overlap.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (get_, create_, cancel_, check_, update_, search_). No mixed conventions or stylistic deviations exist.

Tool Count5/5

13 tools is well-scoped for the guest-facing restaurant domain, covering menu browsing, search, cart, orders, reservations, store info, and policies. Each tool is justified and the count is within the ideal range.

Completeness4/5

Core lifecycle coverage is solid: menu, cart, order placement/status, reservations, and availability are all covered. The only notable gap is the absence of an order cancellation tool, but this may be intentional and does not block primary workflows.

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