Skip to main content
Glama

Club OS by Cotlet

Configure belt programs levels ranks in Club OS

club_os_configure_belt_programs_levels_ranks
Read-onlyIdempotent

Configure belt programs levels ranks 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_belt_programs_levels_ranks"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description is fully consistent, reinforcing that the tool opens nothing by itself and only returns guidance. The note that Club OS's official API requires emailing support for credentials adds useful context about an alternative route not covered by annotations. It does not describe output shape beyond "step by step (screens, buttons, fields)", which is adequate given there is no output schema.

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 core behavior and the browser-tool handoff are front-loaded, which is good. However, "from ChatGPT, Claude or any AI agent" is filler, and the trailing sentence about the official API is tangential to the tool's own function, diluting an otherwise tight definition.

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 description covers what it returns, what it does not do, and how to act on the result. The only shortfall is that it never states the shape or limits of the returned instructions (length, location-specific variance).

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 there is nothing for the description to disambiguate. Baseline 4 applies; no parameter-level detail is missing because none exists.

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 verb and resource ("Configure belt programs levels ranks") scoped to "the user's own Club OS account", and crucially clarifies that the tool returns step-by-step instructions rather than performing the action. It does not explicitly contrast itself with the many sibling club_os_configure_* tools, so an agent must rely on the resource name alone to distinguish it from e.g. club_os_configure_kpi_goals.

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 a clear two-step workflow: call this tool to get the procedure, then execute it with the cotlet_browser_* tools in the Cloud Browser. The "opens nothing by itself" clause tells the agent this is not a one-shot action. It lacks an explicit exclusion (e.g. when to skip this and call the API path instead), which keeps it below a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources