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MaCalculatriceEnLigne

Calculate Meat Cooking

calculate_meat_cooking
Read-onlyIdempotent

Compute meat cooking time and target internal temperature by cut and doneness. Use for kitchen prep. Inputs: meat type, weight kg, doneness. Returns oven time and target temp. See list_bundles for related 'cuisine' calculators.

Input Schema

NameRequiredDescriptionDefault
meatYesMeat type
donenessNoDonenessmedium
weight_kgYesMeat weight kg

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

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description's contribution is limited to "returns oven time and target temp," which the output schema already conveys, so it adds little behavioral context beyond the baseline.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first two sentences are tight and front-loaded, but the closing sentence redirects the agent to list_bundles for "'cuisine' calculators," which is promotional noise rather than selection help and points away from the true sibling calculate_meat_cooking_time.

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 a full output schema and rich annotations, return values and safety need not be explained, so the description is adequate on those axes. It falls short on the one thing structured data cannot supply: disambiguating this tool from the extremely similar cooking-calculation siblings in a list of 300+ tools.

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 enums are documented in the schema, so the schema carries the meaning. The description merely re-lists the inputs (meat type, weight kg, doneness) without adding units, defaults, or range constraints beyond what is already there - the baseline 3.

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 gives a specific verb and resource: compute meat cooking time plus target internal temperature, scoped by cut and doneness. That is clear enough to select the tool, but it does nothing to separate it from the near-identical sibling calculate_meat_cooking_time, nor from calculate_cooking_time or convert_cooking.

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?

"Use for kitchen prep" is the only usage guidance and is essentially a restatement of the domain. There is no when-not guidance and no mention of the obvious alternative calculate_meat_cooking_time, which is the one decision an agent actually has to make here.

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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