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tresor4k

macalc

calculate_density

Given any two of mass, volume, or density, calculate the third using ρ=m/V. Ideal for materials science, chemistry, and fluid dynamics.

Instructions

Compute density, mass, or volume given the other two. ρ=m/V. Use for materials, chemistry, fluid dynamics. Inputs: any 2 of (mass, volume, density). Returns the third. See list_bundles for related 'science' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mass_kgNoMass kg
volume_m3NoVolume m³
densityNokg/m³

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.
Behavior4/5

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

With no annotations, the description fully explains the tool's behavior: accepts any 2 of 3 inputs and returns the third. It is transparent about the computation formula (ρ=m/V). Missing error handling details, but overall clear.

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?

Three sentences: purpose, formula/use, input/output + pointer. Front-loaded, no filler. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given low complexity, full schema coverage, and presence of output schema, the description is complete. It explains the core logic, required inputs, and related tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with unit descriptions. The description adds critical context: that exactly two of the three parameters are required, and which combination is valid. This exceeds the schema's 'optional' declarations.

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 'Compute density, mass, or volume given the other two' with a specific verb and resource. It distinguishes from sibling calculators like calculate_density_convert by focusing on the core relationship rather than unit conversion.

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?

Provides explicit use cases ('materials, chemistry, fluid dynamics') and directs to related tools via 'See list_bundles'. Does not explicitly exclude alternatives but gives sufficient context.

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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