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MaCalculatriceEnLigne

Calculate Compost Volume

calculate_compost_volume
Read-onlyIdempotent

Compute compost volume produced from kitchen and garden waste over a year. Use for compost bin sizing. Inputs: household size, garden size m². Returns L/year and recommended bin volume. See list_bundles for related 'jardinage' calculators.

Input Schema

NameRequiredDescriptionDefault
depth_cmNoCompost layer depth in centimeters (default 5cm)
surface_m2YesSurface area in square meters

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, openWorldHint=false, and destructiveHint=false. The description adds that it returns L/year and recommended bin volume, but an output schema exists and no auth, rate-limit, or other behavioral constraints are disclosed. It adds some context but not much beyond annotations and output schema.

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 sentences, front-loaded with the main purpose, then usage and related tools. The statement about return values is somewhat redundant because an output schema exists, but overall the text is tight.

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?

For a low-complexity calculator with a complete input schema, output schema, and annotations, the description covers most needs. However, the inaccurate input list ('household size') reduces completeness and could confuse an agent about the actual required parameters.

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?

Schema coverage is 100%, so baseline would be 3, but the description lists 'household size' as an input when no such parameter exists, and it omits the schema's depth_cm parameter. This actively misleads about the required inputs despite the schema being complete.

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: computing compost volume from kitchen and garden waste over a year. The purpose is clear and distinguishes it from generic volume calculators in the sibling list.

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?

Explicitly says to use it for compost bin sizing and points to list_bundles for related 'jardinage' calculators. It gives clear context but does not state when not to use it or name a direct alternative.

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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