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Simulate a call with the Lobby receptionist

simulate_receptionist_call

Simulate a phone call with a business receptionist: practice greetings, booking flows, and lead capture with automatic English/Spanish detection by providing up to 6 caller lines.

Instructions

Role-play a phone call with Lobby's receptionist call engine — the same pipeline behind the product demo: greeting, booking flow, lead capture, and automatic English/Spanish detection (live calls add a full AI brain on top). You play the caller: pass each thing the caller says, get the full transcript and outcome back. Free, text-only, max 6 caller lines.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
businessNoBusiness name the receptionist answers for. Default: Lobby Demo Services.
callerSaysYesThe caller's lines, in order. Try Spanish to hear the language switch — e.g. ['Hola, necesito una cita para mañana.']

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
bookedNo
outcomeYes
languageYesLanguage the receptionist detected and answered in.
hearItLiveNoPhone number to call to experience the same receptionist with a real voice.
transcriptYes
leadCapturedNo
Behavior4/5

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

With no annotations, the description carries the burden. It discloses the simulation nature (free, text-only, max 6 lines) and notes language detection and live call differences. No destructive behavior is implied, but side effects are absent.

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?

Two sentences that are front-loaded with purpose and capabilities, no fluff. Every sentence adds value.

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?

Given the output schema exists (though not shown), the description mentions getting full transcript and outcome. It covers usage constraints and basic behavior, but could mention authentication or rate limits if applicable.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds value by explaining the 'callerSays' array order, suggesting Spanish for language switch, and providing an example. The 'business' parameter default is noted.

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 clearly states the tool simulates a phone call with Lobby's receptionist call engine, specifying the pipeline (greeting, booking, lead capture, language detection). It distinguishes from sibling tools like calculate_missed_call_cost by focusing on simulation.

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?

The description explains the user plays the caller and passes each thing they say, receiving the transcript and outcome. It mentions free, text-only, max 6 caller lines, but does not explicitly state when not to use or list alternatives.

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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