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Place a phone call

place_call
Destructive

Place a real outbound phone call to a US business to carry out a stated task, such as making a reservation or asking a question, and return a call id. Every invocation dials: there is no lookup, preview or dry-run mode, and a question about a business is not answered by this tool. The call is billed and cannot be un-placed. Poll get_call_result with the returned id for the transcript and outcome. A repeat of the same number, brief and language within two minutes is absorbed rather than placed again: it comes back as duplicate_call, carrying the id of the call that was already accepted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
briefYes
languageNoauto
target_phoneYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare destructiveHint, idempotentHint=false, openWorldHint and readOnlyHint=false, so the safety profile is partly structured. The description adds genuinely non-structured behavior: the call is billed, cannot be un-placed, always dials with no dry-run, and a repeat within two minutes is absorbed and returns duplicate_call with the prior id. It stops short of saying anything about auth requirements or failure modes beyond duplication.

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?

Purpose is front-loaded in the first clause, followed by constraints, the follow-up tool, and the dedup edge case in descending order of importance. Every sentence carries distinct operational information with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

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 supplies the return contract itself: a call id on success and a duplicate_call shape with the already-accepted id. Combined with the polling instruction and the billing/dedup caveats, an agent has everything needed to call and interpret this tool.

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 parameter burden. It implies brief is the stated task and references language and target_phone only inside the dedup rule ('same number, brief and language'), but never defines the expected brief format, the language value set, or the target_phone format, so the compensation is partial.

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?

States a specific verb and resource ('Place a real outbound phone call to a US business') plus the returned artifact (a call id). It also explicitly carves out territory belonging to a sibling: 'a question about a business is not answered by this tool', which separates it from answer_question.

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?

Gives when-to-use (carry out a stated task like a reservation), when-not (no lookup, preview or dry-run; not for questions), and the follow-up path (poll get_call_result with the returned id). The two-minute duplicate window and duplicate_call outcome tell the agent exactly how repeats behave.

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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