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Read a running/race readiness baseline

readiness_baseline

Combine all key performance indicators—lactate threshold, VO2max, race predictions, fitness trend, endurance score, power bests—into trends to establish a baseline for race-readiness questions.

Instructions

Combine the full performance-indicator set — running lactate threshold (pace/power/HR), VO₂max, race predictions, fitness trend, endurance score, and FIT-derived power bests/coverage — as trends in one call. Use this before any single-activity comparison for race-readiness or fitness-target questions. Requires athleteId from list_athletes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sportNo
endDateNo
athleteIdYes
startDateNo
Behavior3/5

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

With no annotations, the description carries the burden of explaining behavior. It does clarify that this is a read/combine call requiring athleteId and that it returns trends. But it does not state whether there are side effects, how much historical data is needed, or how the response is structured.

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 three sentences with no filler. The first sentence front-loads the core behavior and enumerates the included indicators, the second gives usage guidance, and the third states the prerequisite. Every sentence earns its place.

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?

For a tool with no annotations, no output schema, and 0% parameter documentation, this description leaves three optional parameters unexplained and never describes the response. The usage cue is helpful, but an agent still lacks enough information to call the tool correctly for non-default sport or date inputs.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. It only mentions athleteId and where it comes from; sport, startDate, and endDate are never explained, and their role in producing trends is left entirely implicit.

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 uses a specific verb, 'Combine', with a clearly identified resource: the full performance-indicator set presented as trends in one call. It also distinguishes itself from single-activity comparison tools by positioning this as the aggregate, readiness-level call.

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?

It explicitly states when to use the tool: 'before any single-activity comparison for race-readiness or fitness-target questions.' It also names the prerequisite required for invocation: athleteId from list_athletes. However, it does not name specific alternative siblings or state 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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