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Add client

add_client
Destructive

Add a client to the business's client list. Adds a client as Add client in the Client list does: name, email, mobile and gender. With appointment_messages (default true) Fresha sends the client booking confirmations and reminders to the email and mobile given; marketing (default false) records consent to marketing messages. Nothing is sent when the client is added.

Input Schema

NameRequiredDescriptionDefault
emailNoEmail.
phoneNoMobile number with country code, e.g. +44 7700 900123.
genderNoGender.
last_nameNoLast name.
marketingNoThe client agreed to marketing messages. Default: false.
first_nameYesFirst name.
appointment_messagesNoLet Fresha send this client booking confirmations and reminders by email, SMS and WhatsApp. Default: true.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare non-read-only, destructive, open-world and non-idempotent, and the description adds genuinely new behavioral context: nothing is sent to the client on creation, and the flags record consent rather than trigger messaging. It still omits the consequence of idempotentHint=false, i.e. that retries or existing matches may create duplicates.

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 scope statement is correctly front-loaded, but the sentence "Adds a client as Add client in the Client list does" is garbled and redundant, and the flag explanations are dense. Several clauses restate what the schema already says rather than earning their place.

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

Completeness3/5

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

With seven parameters and no output schema, an agent still lacks two things: which fields beyond first_name are required (only the schema reveals this), and what the call returns (a client id?). The behavioral notes are solid, but the definition stops short of fully equipping a caller for a creation operation.

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 100%, so the schema already documents all seven parameters and their defaults. The description adds real meaning only for appointment_messages and marketing (what consent they record and that Fresha sends confirmations/reminders), while repeating first/last name, email, mobile and gender with no extra syntax or constraint detail.

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 opening sentence states a specific verb and resource ("Add a client to the business's client list") and enumerates the fields captured (name, email, mobile, gender), making it trivially distinguishable from siblings like list_clients, get_client and create_appointment.

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

Usage Guidelines3/5

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

Usage is only implied by the verb – there is no explicit statement of when to use this versus create_appointment or how to handle an existing client. The description does clarify the two boolean flags' intent (booking messages vs marketing consent), which helps an agent configure the call but not decide to make it.

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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