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VoiceDesk AI

Prepare an onboarding request

create_onboarding_request
Idempotent

Prepare onboarding for a US business that wants VoiceDesk AI, with its owner's consent. VoiceDesk reviews it and sends the owner a signup link; the owner chooses and pays for a plan themselves. Creates no account, subscription, phone number or charge. Returns a tracking reference and a one-time status_token.

Input Schema

NameRequiredDescriptionDefault
emailYes
phoneYes
messageNo
websiteNo
industryNo
timezoneNo
plan_codeNo
contact_nameYes
business_nameYes
idempotency_keyNo
consent_to_contactYes
expected_monthly_minutesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: it explicitly says no account, subscription, phone number, or charge is created, which resolves the real risk of a mutation tool that is non-destructive but still has external effects. It also discloses the return values (tracking reference and a one-time status_token), which the annotations cannot convey.

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?

Four short sentences, front-loaded with the core action and scope, followed by the outcome and the explicit non-effects. Nothing is redundant or padded.

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 outcome and side-effect story, and though there is no output schema, it names the return values. However, for a 12-parameter mutation tool with 0% schema coverage, the absence of any parameter guidance leaves a material hole an agent would have to fill by 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 description coverage is 0% across 12 parameters, so the description carries the full burden and largely fails. Only consent ('with its owner's consent') maps to a field; plan_code, idempotency_key, expected_monthly_minutes, timezone, industry, and website are never explained, leaving the agent to guess at their semantics.

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?

States a specific verb and resource: prepare an onboarding request for a US business wanting VoiceDesk AI. It is clearly distinguishable from the demo-oriented siblings (create_demo_request/get_demo_status) by framing this as a pre-signup lead, though it never names those siblings explicitly.

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?

Implies the use context well: the owner must consent, VoiceDesk reviews and sends a signup link, and the owner picks and pays for a plan themselves. That tells the agent this is a pre-sales handoff, not provisioning. It stops short of explicit when-not or named-alternative guidance against the sibling tools.

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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