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MaCalculatriceEnLigne

Calculate Pool Volume

calculate_pool_volume
Read-onlyIdempotent

Compute swimming pool water volume in m³ and liters. Use for pool maintenance dosing. Inputs: shape, dimensions. Returns volume m³ and L. See list_bundles for related 'vie-quotidienne' calculators.

Input Schema

NameRequiredDescriptionDefault
shapeYesShape
depth_mYesAvg depth m
width_mNoWidth m
length_mNoLength m
diameter_mNoDiameter (round)

Output Schema

NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered by structured data. The description adds the return units (m³ and L), which is mildly useful, but says nothing about validation, shape/dimension mismatches, or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with purpose, then usage, then inputs/outputs, then a cross-reference. Each sentence carries information, though the list_bundles pointer is somewhat tangential to invoking this tool correctly.

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?

With an output schema present, the description need not detail return values, and annotations cover the safety profile. The remaining gap is the shape-to-dimension mapping, which is only partially inferable from the schema; otherwise an agent has enough to call it correctly.

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 description coverage is 100%, so the baseline is 3. The description only summarizes 'shape, dimensions', which adds nothing the schema's enum and per-field descriptions do not already provide; it notably does not clarify which dimension fields are required for which shape (e.g., diameter for round).

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?

States a specific verb and resource ('Compute swimming pool water volume in m³ and liters'), which cleanly separates it from the many other volume calculators in the sibling list (calculate_aquarium_volume, calculate_volume, calculate_compost_volume). The units are named up front, so an agent can identify the tool without opening the schema.

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?

'Use for pool maintenance dosing' gives one concrete usage context, which is more than nothing. However, no alternatives or exclusions are named, and the obvious sibling for the same domain (calculate_pool_chlorine) is not referenced even though it would be the natural next step after computing volume.

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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