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Everfit: Invite client

everfit_invite_client

Everfit: Add a client and email them an invite to set up the Everfit app. Adds a client with first name, last name, email and type, and Everfit emails them an invite right away to set up their profile. By default you are their coach; owners and admins can assign another coach. By default you confirm each call; you can switch that off for this tool. Reaches other people: confirm with the user before each call. Needs the user's Cotlet API key with access to this app.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoonline, in_person or hybrid. Default: online.
emailYesClient email; the invite goes here.
coach_idNoAssign another coach. Owners and admins only. Default: you.
last_nameYesLast name.
first_nameYesFirst name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations mark it non-read-only and open-world, and the description adds the concrete consequences: an invite email is sent immediately to a real person, the tool reaches other people so user confirmation is required before each call, and it needs a Cotlet API key with app access. These are material behavioral facts beyond the annotation flags.

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

Conciseness4/5

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

Front-loaded with the core action and its email side effect, then defaults, then confirmation policy. Four sentences with little waste, though the confirmation and API-key sentences are harness boilerplate rather than tool-specific detail.

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 mutation tool with no output schema, it covers the important ground: what is created, what external message is sent, who the coach is, and the auth/confirmation requirements. Remaining gaps (return value, failure behavior when the invite email bounces) are minor for an invite tool.

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% and the schema already documents the type default, the coach_id default ('you') and the owners/admins restriction, so the description largely restates structured data. It adds the framing that 'by default you are their coach', but no additional format or edge-case meaning for the five parameters.

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 states a specific verb+resource (add a client) plus the distinguishing side effect (Everfit emails an invite to set up the app), which separates it from sibling client tools like everfit_add_client_to_autoflow and everfit_get_client. An agent can tell exactly what this call accomplishes without opening the schema.

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?

It gives clear operating context: who becomes the coach by default, that only owners/admins may override via coach_id, and that each call is confirmed by default and can be switched off for this tool. It stops short of naming explicit alternatives or when-not-to-use conditions, so it is clear context rather than full routing guidance.

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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