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tresor4k

macalc

calculate_raised_bed_soil

Calculate the exact soil volume needed to fill a raised garden bed. Enter length, width, and depth to get cubic meters, bag count, and a recommended mix of compost, topsoil, and sand.

Instructions

Compute soil volume needed to fill a raised garden bed. Use for gardening setup. Inputs: length, width, depth (m). Returns soil m³, bag count, mix recommendation (40% compost / 30% topsoil / 30% sand). See list_bundles for related 'jardinage' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
length_mYesRaised bed length in meters
width_mYesRaised bed width in meters
depth_cmNoRaised bed depth in centimeters (default 30cm)

Output Schema

TableJSON 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).
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states the outputs (soil m³, bag count, mix recommendation) but does not disclose assumptions, edge cases, or how bag count is computed. The depth unit inconsistency (description says m, schema says cm) could mislead.

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 concise with two sentences. The first sentence front-loads the purpose, and the second provides additional context about output and related tools. No unnecessary words.

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?

For a simple 3-parameter tool with an output schema, the description covers the key outputs and suggests related calculators. It could be more precise about units (depth in cm) and bag count details, but it is adequate.

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%, so baseline 3. The description lists input parameters but adds little beyond the schema. Notably, it incorrectly states depth in meters instead of centimeters, which may cause confusion.

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 soil volume for a raised garden bed, specifying the resource and action. It distinguishes from other gardening calculators by focusing on raised beds and including a mix recommendation.

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 says 'Use for gardening setup,' which implies context but does not provide explicit guidance on when to use this tool versus alternatives like calculate_garden_soil or other related calculators. The only alternative mention is 'See list_bundles' without specifics.

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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