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MaCalculatriceEnLigne

Convert Distance

convert_distance
Read-onlyIdempotent

Convert distance between metric (m, km, cm, mm) and imperial (in, ft, yd, mi) plus nautical miles. Use for travel, sport, or engineering. Inputs: value, from, to. Returns: {input, factor}. See list_bundles for related 'conversions' calculators.

Input Schema

NameRequiredDescriptionDefault
toYesTarget unit
fromYesSource unit
valueYesDistance value

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

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is fully covered. The description adds the expected I/O shape ("Inputs: value, from, to. Returns: {input, factor}") but no extra behavioral detail such as rounding precision, invalid-unit handling, or negative-value behavior.

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?

Three short front-loaded sentences: what it converts, where it applies, then I/O and a cross-reference. Tight and scannable, with only the list_bundles pointer being of marginal value.

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?

With a full output schema, complete enum coverage, and annotations covering the safety profile, the description needs only to identify the operation and its scope, which it does. The stated return shape ({input, factor}) looks like a partial guess rather than the converted value, a minor risk given the output schema already defines it.

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% and both enum parameters are documented there, so the schema carries the burden. The description's "Inputs: value, from, to" merely restates the schema and adds no format or constraint detail beyond it; 3 is the correct baseline.

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?

Names the exact operation (unit conversion of distance) and enumerates the full supported unit set, metric and imperial plus nautical miles. This cleanly separates it from ambiguous siblings such as calculate_distance_2d, calculate_flight_distance, and calculate_light_year_distance, which compute distances rather than convert units.

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?

"Use for travel, sport, or engineering" gives domain context but no when-to-use/when-not-to-use logic and does not route the agent between this tool and the other convert_* siblings or calculate_distance_* tools. The mention of list_bundles is a weak cross-reference rather than a selection rule.

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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