Eversports Studio Manager by Cotlet

Configure customer referrals in Eversports Studio Manager

eversports_studio_manager_configure_customer_referrals

Read-onlyIdempotent

Configure customer referrals in the user's own Eversports Studio Manager account from ChatGPT, Claude or any AI agent. Returns how to do it in Eversports Studio Manager step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Eversports Studio Manager Cloud Browser. Eversports Studio Manager's official API: Eversports Studio Manager has an official Provider API, but it is read-only: it reads eight areas (business and venues, schedules, booking details, teachers, products, customers, customer products, and attendance and court bookings) and cannot add, change or cancel anything.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "eversports_studio_manager_configure_customer_referrals"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already mark it read-only, non-destructive, idempotent, and closed-world. The description adds that it opens nothing itself, returns instructions, and that the official Provider API is read-only and cannot add/change/cancel anything. That is useful behavioral context and is consistent with annotations.

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?

The description is front-loaded with the purpose and then the execution path. It is somewhat verbose in the official-API rationale and the 'ChatGPT, Claude or any AI agent' phrasing, but every sentence supports correct use.

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

Completeness5/5

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

For a zero-parameter, read-only instruction tool with no output schema, the description covers purpose, return style (step-by-step screens/buttons/fields), and the required follow-up browser tools. Nothing essential is missing.

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?

There are no parameters, so the baseline is 4. The description adds no parameter details because none exist; the empty schema is fully sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource ('Configure customer referrals in the user's own Eversports Studio Manager account') and clarifies that the tool returns step-by-step instructions rather than performing the action. It does not explicitly distinguish this from closely named siblings like create_a_referral_code_your_bonus or export_customer_referrals, so it misses full sibling differentiation.

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 explains the workflow: call this to get step-by-step screens/buttons/fields, then use cotlet_browser_* tools in the Cloud Browser to actually make changes. It does not name when not to use it or point to specific sibling alternatives, but the context is clear.

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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