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MaCalculatriceEnLigne

Calculate Ideal Gas

calculate_ideal_gas
Read-onlyIdempotent

Solve PV=nRT. Provide any 3 of: pressure_pa, volume_m3, moles, temperature_k. R=8.314. Returns: {error}. See list_bundles for related 'science' calculators.

Input Schema

NameRequiredDescriptionDefault
molesNoAmount in mol
volume_m3NoVolume in m³
pressure_paNoPressure in Pa
temperature_kNoTemperature in K

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the requirement of supplying exactly three inputs and mentions returning an error object, but does not elaborate on error conditions or edge cases. With annotations covering the core behavior, a 3 is appropriate.

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 short, front-loaded sentences with no wasted words. The final sentence about list_bundles is slightly tangential but still useful for discovery; overall it is efficient and well-structured.

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 calculator with annotations and an output schema, the description covers the essential input pattern and points to related tools. It could mention what happens if more than three inputs are provided or clarify the return shape, but the output schema presumably handles those details, making the definition nearly complete.

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 description coverage is 100%, so each parameter's meaning (e.g., 'Pressure in Pa') is already documented. The description lists the parameter names but adds no further semantic detail; baseline 3 applies when the schema handles parameter documentation.

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?

States the specific formula 'Solve PV=nRT' and lists the four variables, making the tool's purpose unmistakable. It does not explicitly differentiate itself from other physics calculators (e.g., calculate_pressure_convert), but the formula is specific enough that an agent can identify its niche.

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?

Instructs to 'Provide any 3 of' the four variables, which clarifies the invocation pattern. However, it offers no guidance on when to choose this tool over alternatives like calculate_pressure_convert or calculate_volume, and the pointer to 'list_bundles' is for discovery rather than usage 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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