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Entervista

Approve (customer said yes)

approve_request

Use only after the customer explicitly approves the total / quote / final price. Sends it to the business. When offered_slots is present, pass the customer's chosen slot_start. If the business takes online payment, the result is status awaiting_payment with a payment_url: give that link to the customer; they pay on that page themselves.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refYes
slot_startNo
customer_tokenYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Goes well past the annotations (readOnly=false, openWorld=true, non-idempotent) by disclosing the state machine outcome: the request is submitted to the business, and if online payment is enabled the result is awaiting_payment with a payment_url the agent must hand to the customer. This is exactly the kind of operational detail annotations cannot express.

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 gating condition and then the two runtime branches. Every sentence earns its place and none repeats the schema or annotations.

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?

With no output schema, the description correctly compensates by describing the resulting status and payment_url. The only gap is the unexplained ref and customer_token parameters, which an agent must infer from the sibling toolchain.

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 0%, so the description must carry the burden for all three params. It does well for slot_start (pass the chosen slot_start when offered_slots is present), but ref and customer_token receive no semantic explanation at all, leaving two required-ish inputs undocumented.

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 (approve) plus resource (the request/quote), with the precondition and the downstream effect ('Sends it to the business') spelled out. It is clearly distinct from cancel_request and request_quote, though it never names a sibling explicitly to route the agent.

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?

'Use only after the customer explicitly approves the total / quote / final price' is an explicit when/when-not gate, and the offered_slots clause tells the agent exactly what to pass in that condition. Nothing about the trigger is left to inference.

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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