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tresor4k

macalc

calculate_buoyancy

Compute buoyancy force and determine if an object floats or sinks using Archimedes principle. Input mass, volume, and fluid density.

Instructions

Compute buoyancy force, displaced volume, or floating analysis (Archimedes). Use for physics or shipping. Inputs: object mass/volume, fluid density. Returns buoyant force and float/sink verdict. See list_bundles for related 'science' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
volume_m3YesObject volume m³
fluid_densityNoFluid density kg/m³
object_massYesObject mass kg

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 must disclose behavior. It states the tool computes and returns results, implying read-only behavior. However, it does not discuss edge cases, error handling, or any state changes. For a straightforward physics calculator, this is adequate but not thorough.

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 concise at two sentences plus a reference, with no unnecessary words. It front-loads the core purpose and then adds usage context. While it could be more structured (e.g., listing outputs explicitly), it earns its length.

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?

Given the tool's simplicity (3 parameters, 2 required, output schema present), the description covers the essential aspects: what it computes, inputs, outputs, and general usage domain. It is complete enough for an agent to invoke the tool correctly.

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?

The input schema has 100% description coverage, with each parameter having a clear description (e.g., 'Object volume m³', 'Fluid density kg/m³'). The description adds 'Inputs: object mass/volume, fluid density' but does not provide additional meaning beyond what the schema already offers.

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 tool computes buoyancy force, displaced volume, or floating analysis using Archimedes principle. It specifies usage for physics or shipping and mentions outputs (buoyant force, float/sink verdict). The reference to 'science' calculators in list_bundles helps differentiate from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

The description suggests using the tool for physics or shipping but does not provide explicit guidance on when not to use it or direct alternatives. The mention of list_bundles for related calculators is vague and doesn't name specific sibling tools that might be more appropriate in certain scenarios.

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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