call_place

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

With no annotations provided, the description fully carries the behavior disclosure burden. It explains consent handling, return values like consent_required and awaiting_mid_call_answer, the absence of a confirm boolean, and dry-run simulation behavior. These details go beyond what annotations would typically provide and give the agent a realistic model of the tool's runtime behavior.

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

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

The description is dense but every sentence provides actionable information: purpose, intents, language, slot requirements, consent flow, mid-call answer flow, confirm boolean absence, and dry-run behavior. There is no fluff or repetition, and it is front-loaded with the core purpose. This is an excellent balance of detail and brevity.

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

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex tool involving consent workflows, mid-call interactions, and dry-run behavior. The description covers the critical operational flows and return states. While it does not spell out the success return shape, an output schema is present, so that information is not required in the description. The description is sufficiently complete for safe and correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no descriptions (0% coverage), so the description must compensate. It explains the intent values, the required slot (question) for inquiry, and that language is restricted to 'en'. It also clarifies that there is no confirm boolean. However, it does not explain the meaning of all parameters (e.g., kind, venue, phone, slots keys), leaving some gaps for a few parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Place a structured outbound VOYGR call to a venue phone.' This clearly states what the tool does and distinguishes it from sibling tools like approve_call or answer_mid_call, which are follow-up actions. It further clarifies the two intents (inquiry and info_gathering), leaving no ambiguity about the primary function.

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

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

The description provides explicit usage guidance, including when to use alternative tools: if consent is required, 'call approve_call'; if a mid-call question arises, 'answer_mid_call'. It also sets a clear precondition for the inquiry intent (slots must include a question) and states that party_size/date/time alone are insufficient. This gives the agent actionable decision rules.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.