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calcular_porcentaje_panadero

Read-only

Calcula el porcentaje del panadero (baker's percentage) para una receta. La harina siempre es 100%; cada ingrediente se expresa como % de su peso. Detecta el agua automáticamente para calcular la hidratación. Los prefermentos (masa madre, poolish, biga, esponja) hay que marcarlos con prefermento_hidratacion_pct: son harina y agua ya mezcladas, y sin declararlos la hidratación sale más baja que la real.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
harina_gYesPeso de la harina que se pesa aparte, en gramos (sin la que va dentro de un prefermento).
ingredientesYesLista de ingredientes además de la harina.
peso_porcion_gNoPeso de cada pieza/porción en gramos. Opcional: calcula el número de porciones.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / harina_g / description
      Previous value: -"Peso de la harina en gramos (siempre 100% en el sistema del panadero)."New value: +"Peso de la harina que se pesa aparte, en gramos (sin la que va dentro de un prefermento)."
    • addedInput schema / properties / ingredientes / items / properties / prefermento_hidratacion_pct
      Added value: +{
+  "description": "Solo para prefermentos: su hidratación en % sobre su propia harina. 100 = mitad harina y mitad agua (masa madre líquida, poolish); 50-60 para biga o madre firme. Omitir en ingredientes normales.",
+  "minimum": 0,
+  "type": "number"
+}
  2. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already mark the tool as read-only, and the description adds real behavioral context by explaining that water is detected automatically and, importantly, that hydration will be lower than the real value if preferments are not declared. This goes beyond the annotations without contradicting them.

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 short, focused, and front-loaded: the purpose and core formula come first, followed by the crucial preferment caveat. Every sentence adds information and there is no filler.

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 read-only calculator with a complete parameter schema, the description covers the core behavior, the mathematical rule, and the key edge case about preferments. The main gaps are the lack of an explicit return format and no mention of the closely related sibling calcular_hidratacion_pan, but neither prevents a competent agent from using the tool 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?

The schema already covers all three parameters at 100%, so the baseline is 3. The description adds value by explaining the baker's percentage model, the role of flour, and the meaning of prefermento_hidratacion_pct, including the risk of omitting it. That counts as meaningful semantic enrichment.

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?

Describes a clear verb and resource: calculates baker's percentage for a recipe, and states that flour is 100% and each ingredient is expressed as a percentage of its weight. It is clearly about baking recipes, but it does not explicitly distinguish it from overlapping siblings such as calcular_hidratacion_pan, so it falls just short of full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context: the tool is for recipes, automatically detects water to calculate hydration, and explicitly instructs how to handle preferments. It does not name alternative tools or use cases, but the conditions given are enough to guide correct usage.

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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