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VictorForV

intervals-mcp

by VictorForV
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_best_efforts

Retrieve peak sustained effort values for heart rate, pace, or power across durations from 5 seconds to 90 minutes. Compare current athletic form with past peaks to gauge fitness changes.

Instructions

Best-effort curve for a sport: the athlete's peak sustained values.

    kind is hr, pace or power. Returns the best value held for 5s, 15s, 30s,
    1m, 5m, 10m, 20m, 30m, 1h and 1h30m over the window, which defaults to
    the last 12 months. Use it to compare current form against past peaks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
newestNo
oldestNo
sport_typeNoRun

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure and does a solid job: it names the exact durations returned, states that the window defaults to the last 12 months, and clarifies kind values. It does not describe read-only safety or response format, but it is not misleading.

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 compact and front-loaded: it opens with the core output, then lists kind, durations, window default, and purpose. Every sentence contributes useful information and there is no filler.

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?

It is adequate for a basic default call because the required kind parameter is explained and other parameters are optional. However, with no output schema, no annotations, and no date-format guidance for newest/oldest, an agent cannot fully anticipate custom-window behavior without guessing.

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

Parameters2/5

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

The schema has 0% description coverage, so the description must compensate. It only documents kind ('hr, pace or power') and vaguely hints at the window default; newest, oldest, and sport_type are left entirely to inference from their names/default values.

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 identifies the resource and output: an athlete's best-effort curve with peak sustained values for hr, pace, or power, over named durations. It is specific enough to understand the tool, but it does not explicitly distinguish it from the close sibling get_best_effort_chart.

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?

It offers a concrete intended use: 'Use it to compare current form against past peaks.' However, it gives no when-not-to-use guidance and does not mention any alternative tool, so an agent is left to infer routing among sibling tools.

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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