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CoachingPortal by Cotlet

Generate meal plan draft in CoachingPortal

coachingportal_generate_meal_plan_draft
Read-onlyIdempotent

Generate meal plan draft in the user's own CoachingPortal account from ChatGPT, Claude or any AI agent. Returns how to do it in CoachingPortal step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's CoachingPortal Cloud Browser. CoachingPortal's official API: CoachingPortal publishes no public API.

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": "coachingportal_generate_meal_plan_draft"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, which the description is consistent with. Beyond that, the description adds that it opens nothing by itself and hands execution to browser tools, plus the notable fact that CoachingPortal has no public API. It does not describe output length, failure modes, or what happens without a connected Cloud Browser.

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?

Three front-loaded sentences that convey the key facts early. There is mild redundancy (repeating 'CoachingPortal' throughout) and the dangling fragment 'CoachingPortal's official API: CoachingPortal publishes no public API' is awkwardly formatted, but nothing is wasted.

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 definition must explain what is returned and what to do next, which it does (step-by-step instructions; then use cotlet_browser_* tools). Missing only edge-case context such as Cloud Browser session requirements or what happens when the user is not signed in.

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 there is nothing for the description to disambiguate; the baseline of 4 applies. The description does not need to describe arguments and correctly focuses on behavior instead.

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 (generate meal plan draft) and, crucially, discloses that the tool does not actually perform the action but returns step-by-step CoachingPortal instructions. The 'generate' name could mislead, but the description corrects it immediately. It does not name sibling tools like create_meal_plan or assign_meal_plan, so differentiation is only implicit.

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?

Gives a clear usage sequence: call this to get screens/buttons/fields, then execute with cotlet_browser_* tools in the Cloud Browser. This is actionable guidance absent from the name or schema. It lacks explicit exclusions (e.g., when to use create_meal_plan instead) or prerequisites such as an active Cloud Browser session.

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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