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Glama

Servd Agentic Ordering

Validate and price cart

validate_cart
Read-onlyIdempotent

Validate a proposed cart and calculate authoritative lines, discounts, fees, tax and total without creating an order. Call this immediately before asking the diner to confirm. Send only the minimum diner contact and fulfillment data required for this order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe venue slug returned by find_venues.
itemsNo
combosNo
customerNo
deliveryNo
tip_amountNoMajor currency units.
fulfillmentYes
payment_methodNoonline

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
linesYes
validYes
venueYes
totalsYes
fulfillmentYes
paymentModeYes
confirmationYes
createsOrderYes
requirementsYes
paymentMethodYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already carry readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: no order is created, and the pricing is authoritative (server recalculated). However, it doesn't disclose behavior on invalid carts or failures, though the output schema may cover that.

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 sentences, front-loaded with the core purpose, and no wasted words. The timing instruction and data minimization guidance are packed efficiently into the second sentence.

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?

For a tool with rich input and output schemas plus strong annotations, the description covers the essential purpose, non-mutating behavior, and call timing. It could add a brief note about validation failure behavior, but given the output schema exists, the description is substantially complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25%, so the description carries more responsibility for parameter meaning. It does add some guidance by saying to send only minimum contact and fulfillment data, but it does not explain key parameters like items, combos, customer, delivery, or payment_method. This leaves a significant semantic gap.

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 states a specific verb ('validate'), a specific resource ('proposed cart'), and the exact scope: calculating lines, discounts, fees, tax, and total. It also explicitly distinguishes itself from order creation ('without creating an order'), which separates it clearly from place_order.

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?

The description gives a clear, explicit invocation context: 'Call this immediately before asking the diner to confirm.' This tells the agent when to use it. It doesn't explicitly name alternatives or exclusions, but the 'without creating an order' phrasing implies the key distinction from place_order.

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

A4.3/5.0
Disambiguation5/5

Each tool targets a distinct step in the ordering workflow: venue discovery, venue details, menu retrieval, cart validation, order placement, and order status checking. Even find_venues and get_venue are clearly separated by list/search versus single-venue detail.

Naming Consistency5/5

All tool names follow a consistent lowercase verb_noun pattern: find_venues, get_venue, get_menu, validate_cart, place_order, check_order. The verbs are distinct yet predictable, and there is no mixing of casing or naming styles.

Tool Count5/5

Six tools is well-scoped for an agentic ordering server. Each tool supports a necessary phase of the ordering flow without redundancy or unnecessary bulk.

Completeness4/5

The core ordering lifecycle is covered: discover venues, inspect venue details, fetch menus, validate carts, place orders, and poll order status. The main gap is the lack of a cancel_order or update_order tool, so order management after placement is limited.

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