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MaCalculatriceEnLigne

Calculate Braking Distance

calculate_braking_distance
Read-onlyIdempotent

Compute reaction + braking distance by road condition (dry/wet/icy). Use for driver safety education. Inputs: speed km/h, reaction time s, road type. Returns total stopping distance m. See list_bundles for related 'auto-transport' calculators.

Input Schema

NameRequiredDescriptionDefault
conditionNoRoaddry
speed_kmhYesSpeed km/h

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

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is fully covered. The description adds that this is a pure physics computation returning a distance in meters, which is useful, but it is otherwise thin and inaccurately claims a reaction-time input.

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?

Four short, front-loaded sentences that lead with the computation and end with a discovery pointer; appropriately sized for a simple calculator. One sentence is spent on the inaccurate input list, which detracts slightly from otherwise tight structure.

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

Completeness3/5

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

With annotations, a 100%-covered schema, and an output schema, most of the burden is carried structurally. Still missing: what reaction time the model assumes internally (since it is not an input), and any differentiation from calculate_distance_securite.

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

Parameters2/5

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

Schema coverage is 100%, so the two real parameters (speed_kmh, condition) baseline at 3. However, the description's 'Inputs:' list invents a third parameter ('reaction time s') that does not exist under additionalProperties:false, actively misleading the agent into an invocation that would fail.

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 a specific verb and resource ('Compute reaction + braking distance by road condition') and scopes it to driver safety education, which clearly separates it from the hundreds of unrelated calculate_* siblings. The only blemish is that it advertises an input ('reaction time s') that the tool does not actually accept.

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?

Gives a domain hint ('Use for driver safety education') and routes to list_bundles for related 'auto-transport' calculators, so usage is implied. It never names or excludes a concrete alternative, notably the close sibling calculate_distance_securite (safety distance), leaving the agent to guess which to call.

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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