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Instant Receptionist — a working app in one call

instant-receptionist

Instant Receptionist — a working app in one call — Order a WORKING, branded AI receptionist for any business in one call. Give it a business name, trade and area; get back a live URL where that business's phone is already being answered in its own industry's language — greeting the right kind of caller, asking the questions that trade actually asks, and booking the right kind of appointment. Nothing to install, no account, no card, no phone number (12 MESH/call, a tool · business)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesPayload for instant-receptionist

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Adds valuable context beyond annotations: cost (12 MESH/call), no account/card/phone number required, and the promise of a live URL. With readOnlyHint=false and openWorldHint=true already present, the description enriches rather than duplicates the safety/behavior profile. It does not detail URL persistence or revocation, but the annotations already cover the non-destructive, world-facing nature.

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

Conciseness3/5

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

The description is somewhat verbose, repeating the title phrase and using promotional language. It is front-loaded with the core promise and includes necessary details like cost and no-setup, but it could be trimmed by a sentence or two without losing 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?

For a tool with a single nested parameter and no output schema, the description covers the essential context: what to provide, what you get (a live URL), pricing, and lack of prerequisites. It omits the trade-vertical matching limit and error behavior, but the schema already documents those, so the description is sufficiently complete.

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% and each parameter has a rich description (aliases, defaults, error behavior for trade). The description simply restates the three inputs without adding new format or meaning, so it meets the baseline 3 but does not exceed it.

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 action (order a working, branded AI receptionist) with clear inputs (business name, trade, area) and output (live URL). It distinguishes itself from any sibling tool—no other tool offers this service.

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?

Clearly presents the use case: ordering an AI receptionist for a business. It describes the input/output flow and prerequisites, providing clear context. However, it does not explicitly name alternatives or edge cases where another tool would be preferred, so it stops short of a 5.

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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