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Glama

receptionist-toolkit

by com.lobbyvoices

Write a business phone script

write_phone_script

Writes a professional phone script for a business — greeting, voicemail message, on-hold message, or jingle lines — in English, Mexican Spanish, or both. Returns ready-to-record text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoWhat kind of script to write. Default: greeting.
vibeNoTone of voice. Default: warm.
extraNoOptional details to mention: hours, offers, callback promise.
langsNoLanguages to write. Default: both.
tradeNoIndustry or trade, e.g. plumbing, dental clinic.
businessYesBusiness name (required).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ctaNoOne-line invite to try Lobby, with a signup link.
scriptsYes

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It accurately describes the tool as generating script text, but lacks details on permissions, side effects, or limits. The behavior is straightforward and non-destructive, so a 3 is adequate.

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?

The description is a single, well-structured sentence that front-loads the core action and output. Every piece of information is relevant, with no wasted words.

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?

The description covers the essential aspects: what it writes, languages, and output format. With an output schema present and high schema coverage, it is complete enough for a generative tool, though it omits default values for mode and vibe.

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 the description adds limited extra meaning beyond indicating the script types and languages. The baseline of 3 applies; the description reinforces but does not significantly enhance parameter understanding.

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 writes phone scripts, specifies types (greeting, voicemail, hold, jingle) and languages (English, Mexican Spanish), and notes it returns ready-to-record text, distinguishing it from siblings like write_ivr_menu.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention exclusions or compare with sibling tools, leaving the agent to infer usage from the purpose alone.

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

All receptionist-toolkit toolsInspect
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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct function: cost calculation, prompt generation, demo number retrieval, saving results, hiring decision, call simulation, IVR script writing, and general phone script writing. No overlapping purposes or ambiguous boundaries.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (e.g., calculate_missed_call_cost, write_ivr_menu). The naming is uniform and predictable across all 8 tools.

Tool Count5/5

With 8 tools, the toolkit covers the essential workflows for an AI receptionist system without being bloated or insufficient. The count is well-scoped for the domain.

Completeness5/5

The tool set covers the full lifecycle: analysis (calculate_missed_call_cost, should_i_hire_a_receptionist), creation (write_phone_script, write_ivr_menu, generate_elevenlabs_agent_prompt), simulation (simulate_receptionist_call), access (get_demo_call_number), and saving/sharing (save_my_receptionist). No obvious gaps.

Resources