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tresor4k

macalc

calculate_speed_of_sound

Compute the speed of sound in air based on temperature using the formula c = 331.3 + 0.606·T. Input temperature in Celsius, get speed in m/s. Ideal for physics and audio engineering.

Instructions

Compute speed of sound in air at a given temperature. Use for physics or audio engineering. Formula: c=331.3+0.606·T_C. Inputs: temperature °C. Returns speed in m/s. See list_bundles for related 'science' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
temperature_cYesCelsius

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 discloses the formula, input unit (°C), and output unit (m/s), which is sufficient for a simple calculation. It mentions temperature minimum (-273°C) via the schema, but does not discuss edge cases or precision.

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 extremely concise (two sentences plus a reference to related tools) and front-loads the core purpose, with no redundant information.

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 and presence of an output schema, the description covers inputs, formula, and references for related tools. It is complete enough for an AI agent to use correctly.

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% for the single parameter temperature_c, and the description adds meaning by specifying the unit (°C) and how it is used in the formula (T_C), which is not in the schema description.

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 speed of sound in air at a given temperature', specifying the exact resource and action, and distinguishes it from sibling tools by domain (physics/audio engineering) and formula.

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 provides context ('Use for physics or audio engineering') and references list_bundles for related science calculators, but does not explicitly state when not to use this tool or compare it to alternatives like calculate_wave_properties or other physics tools.

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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