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banananovej-chuan

TrainingPeaks MCP Server

tp_get_workouts

Retrieve your TrainingPeaks workouts by date range, type, and limit to analyze performance metrics like duration, TSS, HR, and power.

Instructions

Get a list of workouts from TrainingPeaks.

Args: start_date: Start date (YYYY-MM-DD). Defaults to 30 days ago. end_date: End date (YYYY-MM-DD). Defaults to today. workout_type: Filter by type (e.g. "Bike", "Run", "Swim", "Strength"). limit: Maximum number of workouts to return (default 20).

Returns workouts with date, type, duration, distance, TSS, HR, and power data. The TP API limits requests to 90 days at a time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateNo
end_dateNo
workout_typeNo
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full burden. It discloses returned data fields (date, type, duration, etc.), defaults, and the 90-day API limit. It doesn't mention whether only completed workouts are returned or auth requirements, but overall transparency is strong.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with Args section, returns statement, and a note on API limit. It is concise with no fluff, each sentence earns its place.

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

Completeness5/5

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

Given no annotations, the description covers parameters, return fields, and a key constraint. It is complete for a list tool; the presence of an output schema further reduces the burden.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description compensates fully. It explains each parameter with defaults, example values for workout_type, and limit default. This adds significant meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get a list of workouts from TrainingPeaks,' specifying the verb (get) and resource (list of workouts). This distinguishes it from siblings like 'tp_get_workout' which retrieves a single workout.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides sensible defaults and example filter values, implying typical usage. However, it lacks explicit guidance on when to use this tool versus alternatives like 'tp_get_planned_workouts' or 'tp_workout_analysis'. No exclusions or alternative recommendations are given.

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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