MaCalculatriceEnLigne

calculate_compost_volume

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

TableJSON Schema

Name	Required	Description	Default
`depth_cm`	No	Compost layer depth in centimeters (default 5cm)
`surface_m2`	Yes	Surface area in square meters

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

B3/5.0

Behavior2/5

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions outputs (L/year and recommended bin volume) but does not state that the tool is read-only, non-destructive, or any other behavioral traits. The description lacks transparency about side effects or constraints.

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 remarkably concise with two sentences that cover the verb, purpose, use case, inputs, outputs, and a pointer to related tools. Every sentence adds value without redundancy.

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?

Given the simplicity of the tool (2 parameters, calculation), the description is incomplete due to the inconsistency between mentioned inputs ('household size') and the actual schema. It does not clarify the output schema beyond vague units, despite an output schema existing. The inconsistency undermines completeness.

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 input schema has 100% description coverage, so the baseline is 3. However, the description introduces 'household size' which is not in the schema, creating confusion. It does not explain 'depth_cm' beyond the schema's own description. The mismatch reduces the value added by the description.

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 states the verb 'Compute' and the resource 'compost volume produced from kitchen and garden waste over a year', and specifies the use case 'compost bin sizing'. However, it mentions 'household size' as an input which does not appear in the schema, causing slight ambiguity. It distinguishes from siblings by referencing '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 Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description advises using the tool for 'compost bin sizing' and suggests seeing 'list_bundles' for related calculators, giving some context on when to use it. However, it does not provide explicit when-not-to-use scenarios or alternatives beyond the bundle reference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All MaCalculatriceEnLigne tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.