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TrainingPeaks MCP Server and API by Cotlet

Comment on workout in TrainingPeaks

trainingpeaks_comment_on_workout
Read-onlyIdempotent

Comment on workout in the user's own TrainingPeaks account from ChatGPT, Claude or any AI agent. Returns how to do it in TrainingPeaks step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's TrainingPeaks Cloud Browser. TrainingPeaks's official API: TrainingPeaks has an API, but only approved commercial partners get it, and it is not available for personal use (checked 5 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": "trainingpeaks_comment_on_workout"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces this with 'opens nothing by itself', which is the critical disclosure for an agent that might otherwise expect a mutation. It also discloses the return shape (step-by-step screens, buttons, fields) despite no output schema. The main gap is that with zero parameters it never explains how the target workout is identified or what happens if the user has multiple workouts.

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 follow-up workflow are front-loaded and easy to parse. However, the closing sentence about TrainingPeaks' partner-only API, including a checked date, is justification for the design rather than information needed to invoke the tool, and it lengthens an otherwise tight definition.

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

Completeness3/5

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

Given no output schema, the description does a good job explaining what is returned and how to act on it. But a tool with zero parameters that targets a specific workout leaves an important hole: how the agent or the returned guide knows which workout to comment on, and whether the user must supply that context in conversation. That ambiguity is unresolved.

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 and the schema is trivially complete, so there is no parameter semantics for the description to add. Baseline 4 applies. Nothing in the description misrepresents the empty input.

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 ('Comment on workout in the user's own TrainingPeaks account') and immediately clarifies that the tool itself returns instructions rather than acting. That reframing is essential and prevents the agent from assuming a write occurred. It does not explicitly name the sibling that actually performs the write beyond the generic 'cotlet_browser_*' family.

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 workflow: call this first to get step-by-step screens/buttons/fields, then execute with the cotlet_browser_* tools. It also explains why browser automation is required (the official API is partner-only, not for personal use), which justifies the approach. It stops short of naming alternatives such as cotlet_app_guide or saying when not to use it.

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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