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Entervista

Place an order

place_order

Draft an order (food/retail). Returns line items, total, a ref and a customer_token. Nothing reaches the business until approve_request. Ask the customer to confirm the total first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
itemsYes
customerYesWho the job/order is for. Use what the customer already gave you; ask only for what a tool says is missing.
fulfillmentYes
requested_timeNoISO datetime; omit for ASAP

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations declare non-read-only, non-idempotent, open-world, non-destructive, but the description adds the crucial trait they do not: this is a draft that has no effect on the business until approval. It also previews the returned ref/customer_token, which helps the agent chain calls.

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 short sentences, front-loaded with the core behavior, then the approval dependency, then the confirmation step. No filler.

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?

Covers the lifecycle and return shape well for a tool with no output schema, but with nested objects and low schema description coverage it leaves key input semantics (slug meaning, fulfillment choice, item/option modeling) to inference.

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 coverage is only 40% across 5 params (4 required, one nested item array and a nested customer object), so the description must compensate and does not. It never explains slug, items, fulfillment, requested_time, or the customer structure beyond a schema-level hint.

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?

Specific verb+resource ('Draft an order') with the domain scoped as food/retail, and it distinguishes itself from the finalizing sibling by noting nothing reaches the business until approve_request. Clear, though it never disambiguates against place_service_request or request_quote in the sibling list.

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?

Gives concrete workflow context: draft here, then approve_request to send, and 'Ask the customer to confirm the total first.' That is real when-to-use guidance, but there is no explicit when-not or comparison against the other request-creation siblings.

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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