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Club OS by Cotlet

Configure custom user fields in Club OS

club_os_configure_custom_user_fields
Read-onlyIdempotent

Configure custom user fields in the user's own Club OS account from ChatGPT, Claude or any AI agent. Returns how to do it in Club OS step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Club OS Cloud Browser. Club OS's official API: Club OS has an official API for its calendar, agreements, leads, follow-ups and KPIs, but credentials come only by emailing Club OS support to set up an account (checked 11 Nov 2026).

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": "club_os_configure_custom_user_fields"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

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?

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, and the description reinforces this with 'opens nothing by itself,' which is consistent and useful. It also discloses the shape of the return (screens, buttons, fields) and the API credential limitation, though it says nothing about length, format, or failure modes of the walkthrough.

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 key facts are front-loaded: what it does, that it does nothing by itself, and which tools to use next. The closing note on Club OS's official API is somewhat tangential and long, but it earns its place by preventing a futile attempt at the API route.

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 zero-parameter, read-only guidance tool with no output schema, the definition covers what it returns and how to proceed, which is enough to invoke it correctly. Minor gap: no indication of the return's structure or granularity beyond the parenthetical '(screens, buttons, fields).'

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?

The tool takes zero parameters, so the schema carries no semantics that the description would need to duplicate; baseline of 4 applies. The description does not need to explain parameter meaning and correctly doesn't try.

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 names a specific resource (custom user fields) and, crucially, clarifies that the tool returns step-by-step instructions rather than performing the change ('Returns how to do it in Club OS step by step... and opens nothing by itself'). That distinguishes it from the configure_* siblings that mutate settings, though it never names a sibling directly.

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 explicit sequencing: call this to get the walkthrough, then actually perform the change with the cotlet_browser_* tools in the user's Cloud Browser. It also rules out the official API path by explaining credentials require emailing support. Clear context, but no explicit 'when not to use' framing.

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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