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Exercise.com by Cotlet

Create and manage locations in Exercise.com

exercise_com_create_and_manage_locations
Read-onlyIdempotent

Create and manage locations in the user's own Exercise.com account from ChatGPT, Claude or any AI agent. Returns how to do it in Exercise.com step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Exercise.com Cloud Browser. Exercise.com's official API: Exercise.com has an official API as a paid add-on: "API access is an additional feature with variable pricing", quoted by your Account Representative for your intended usage (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": "exercise_com_create_and_manage_locations"
  }
}

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/idempotentHint true and destructiveHint false, and the description reinforces this by stating the tool performs no action itself. The added detail about what it returns (screens, buttons, fields) is genuinely useful context beyond the annotations. The trailing note on API pricing is informative but not behavioral.

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 two clauses are front-loaded and efficient, but the final sentence quoting Exercise.com API pricing ('an additional feature with variable pricing', 'checked 11 Nov 2026') is tangential to invoking this tool and reads as padding.

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?

With zero parameters and no output schema, the description supplies what the agent needs: it returns click-by-click instructions and performs no mutation, and the actual work happens via the browser tools. The API pricing aside adds noise rather than needed completeness.

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 no parameters, so the schema carries no semantics to supplement; the baseline is 4. The description doesn't misrepresent any inputs.

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?

States a specific verb and resource ('Create and manage locations in the user's own Exercise.com account') and immediately clarifies the actual output: step-by-step instructions rather than an action. Sibling tasks are distinct businesses (products, packages, sessions), so differentiation is implicit but adequate.

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?

Explicitly says it 'opens nothing by itself' and that the follow-up action is done 'with the cotlet_browser_* tools in the user's Exercise.com Cloud Browser,' which tells the agent exactly where this tool sits in a two-step workflow. It does not state when another Exercise.com guidance tool would be the better pick.

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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