MaCalculatriceEnLigne

calculate_vma

Compute VMA (Maximal Aerobic Speed) from a fitness test result. Use for runners building training plans. Inputs: test type (Cooper 12-min, Luc Léger), result. Returns VMA km/h and zones. See list_bundles for related 'sport' calculators.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`test`	Yes	Test type: cooper (12min run), demi_cooper (6min run), vameval (final speed km/h)
`result_value`	Yes	Distance in meters (cooper/demi_cooper) or final speed in km/h (vameval)

Output Schema

TableJSON Schema

Name	Required	Description
`result`	No	Computed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
`source`	No	Authoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
`formula`	No	Human-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
`reference_url`	No	Link to a calcul2 page documenting the calculation in detail.

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 13, 2026

TDQS

A4.1/5.0

Behavior3/5

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

With no annotations, the description adds 'Returns VMA km/h and zones' which discloses return type beyond schema, but does not cover side effects or limitations (e.g., input validation errors). Adequate but not exhaustive.

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?

Two sentences, front-loaded with purpose, no wasted words. Efficiently conveys core information.

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?

For a calculator tool with output schema (implied), description is complete: states inputs, outputs, and references related tools. No gaps apparent.

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

Parameters3/5

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

Schema coverage is 100%, baseline is 3. Description mentions 'Cooper 12-min, Luc Léger' which slightly expands enum labels but adds no new meaning beyond schema descriptions.

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 it computes VMA from a fitness test result, specifies 'for runners building training plans', and distinguishes from siblings by naming specific test types (Cooper, Luc Léger) and directing to list_bundles for related calculators.

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?

Provides a context ('Use for runners building training plans') and points to list_bundles for related tools, implying when not to use, but lacks explicit exclusions or direct comparisons to alternatives like calculate_vo2max.

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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