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Get a human on the line

get_a_human

A crew member dials the number, works the phone menu, hold and AI receptionist until a real person answers, then connects the key's owner into the live call. Spends credits ($0.30 per crew minute; no extra charge when a person is reached). Company lines only unless the callee gave written consent.

Input Schema

NameRequiredDescriptionDefault
toYesE.164 phone number, e.g. +18015551234.
whyNoOne line on why we're calling.
targetNoWho to ask for.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=false, destructiveHint=false and openWorldHint=true, so the description carries real extra weight: it discloses the cost model ($0.30 per crew minute, no extra charge once a person is reached) and a consent/legal restriction on which numbers may be dialed. It stops short of stating failure behavior—what happens or what is billed if no human is reached, whether calls are recorded, or expected hold duration.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, the mechanism front-loaded before the cost and consent caveats, with almost no filler. Minor friction from the phrase 'the key's owner,' which is not defined anywhere in the definition.

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?

There is no output schema, so the description must convey what a call yields; it explains the connection flow but not what the tool returns (call identifier, status, transcript, success/failure signal) or timing expectations. For an open-world, credit-spending action that is a meaningful gap.

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 coverage is 100%, so all three parameters are already documented inline, establishing a baseline of 3. The description adds only indirect meaning—that 'to' is the company line being navigated and that a 'target' person is who the crew asks for—without new formatting or edge-case guidance beyond the schema.

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 names a concrete actor and action chain: 'A crew member dials the number, works the phone menu, hold and AI receptionist until a real person answers, then connects the key's owner into the live call.' That is far more specific than a restated title and clearly separates it from text/email siblings like send_text or send_email.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives eligibility constraints ('Company lines only unless the callee gave written consent'), which implicitly bounds when the tool may be used, but it never states when to prefer it over send_text, send_email, or knock, nor what to do if the line is a personal number.

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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