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get_race_predictions

Predict race finish times using current fitness data from Garmin Connect to plan training and set realistic goals.

Instructions

Get predicted race times based on current fitness level

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'predicted race times' but does not explain how predictions are generated, what data sources are used (e.g., recent activities, heart rate), whether it requires authentication, or any rate limits. This leaves significant gaps in understanding the tool's behavior.

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 a single, clear sentence that efficiently conveys the core functionality without unnecessary words. It is front-loaded with the main action and reason, making it easy to parse and understand quickly.

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

Completeness2/5

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

Given the complexity of predicting race times and the lack of annotations and output schema, the description is insufficient. It does not cover how predictions are made, what output to expect (e.g., times for specific distances), or dependencies on other data, leaving the agent with incomplete information for effective use.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by explaining the tool's purpose ('based on current fitness level'), which provides context beyond the empty schema, justifying a score above the baseline of 3.

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?

The description clearly states the action ('Get predicted race times') and the basis ('based on current fitness level'), which is specific and informative. It distinguishes itself from siblings like 'set_race_goal' (which sets goals) or 'get_personal_records' (which retrieves past achievements), but it could be more precise about what 'race times' refer to (e.g., distances, types of races).

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing fitness data from other tools), exclusions, or how it differs from related tools like 'calculate_training_paces' or 'get_advanced_running_metrics', leaving the agent to infer usage context.

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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