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tresor4k

macalc

calculate_gravel_quantity

Calculate gravel volume in cubic meters and weight in tonnes for paths, foundations, or drainage. Provide length, width, and depth to get precise material estimates for construction projects.

Instructions

Compute gravel volume (m³) and weight (tonnes) for a surface and depth. Use for paths, foundations, drainage. Inputs: area, depth, gravel density. Returns volume and weight. See list_bundles for related 'construction' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
length_mYesLength m
width_mYesWidth m
depth_cmYesDepth cm

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 exist, so description must bear the burden. It correctly states it returns volume and weight, implying a read-only calculation. However, it inconsistently mentions 'gravel density' as an input, which does not appear in the schema, causing potential confusion about what inputs are expected.

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?

The description is three sentences and relatively concise. It front-loads purpose and outputs, though it could be slightly more structured.

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 simple calculation tool with an output schema, the description provides reasonable completeness. However, the input discrepancy reduces clarity and completeness, making it less reliable for the agent.

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 schema has 100% description coverage (length_m, width_m, depth_cm), but the description adds 'area, depth, gravel density' as inputs. 'Gravel density' is not a parameter, and 'area' is derived (length * width). This discrepancy misleads the agent about expected parameters.

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 explicitly states the tool computes gravel volume (m³) and weight (tonnes) for a surface and depth, with use cases like paths, foundations, and drainage. This clearly differentiates it from hundreds of sibling 'calculate_*' tools.

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?

It provides use contexts ('paths, foundations, drainage') and suggests 'See list_bundles for related 'construction' calculators' as an alternative. However, it does not explicitly state when not to use this tool.

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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