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banananovej-chuan

TrainingPeaks MCP Server

tp_training_zones_distribution

Analyze training time and TSS distribution across intensity zones to identify polarized, pyramidal, or threshold-heavy training patterns.

Instructions

Analyze training time and TSS distribution across intensity zones.

Args: start_date: Start date (YYYY-MM-DD). Defaults to {days} days ago. end_date: End date (YYYY-MM-DD). Defaults to today. days: Days to look back if start_date not set (default 30).

Breaks down workouts by IF-based training zones showing how training time and stress are distributed. Helps identify polarized vs pyramidal vs threshold-heavy training patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateNo
end_dateNo
daysNo

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 clearly describes a read-only analytical operation (breaking down workouts by zones) without any mention of side effects or destructive actions. The description adds transparency about what the tool outputs (training time and stress distribution).

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 concise with two clear paragraphs: one for purpose and one for parameter details. Every sentence adds value, and the docstring-style 'Args' section efficiently documents parameters. There is no wasted text.

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?

The description explains what the tool does, its analytical outcomes, and all parameters with defaults. Given that an output schema exists (not shown), the description does not need to detail return values. However, it could briefly mention the output format (e.g., zone breakdowns) for completeness.

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 the description must add meaning beyond the schema. It explains defaults for start_date, end_date, and days (e.g., start_date defaults to {days} days ago, days default 30). This adds significant context that the schema alone does not provide.

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 the tool analyzes training time and TSS distribution across intensity zones, with a specific verb 'analyze' and resource 'training zones distribution'. It highlights the ability to identify training patterns (polarized, pyramidal, threshold-heavy), distinguishing it from siblings like tp_training_load_summary or tp_performance_summary.

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 implies usage for analyzing zone distribution over a date range but lacks explicit guidance on when to use this tool versus alternatives (e.g., tp_fitness_trend, tp_workout_analysis). No exclusion criteria or context for when not to use it are provided.

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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