Burs-IA Utils

Medidas de cocina

convert-cooking

Read-onlyIdempotent

Convierte medidas de cocina entre volumen (taza, cucharada…) y peso (g, oz…) para ingredientes comunes, con densidades típicas. Resultados aproximados. Cuándo: hay que convertir una cantidad entre unidades con factores de definición exactos. No para: convertir volumen entre unidades (convert-volume). Efectos secundarios: ninguno (solo lectura, sin red, sin estado guardado). Determinista: la misma entrada da la misma salida. Límites: entrada JSON de hasta 64 KB, 1 s por llamada, resultado de hasta 1 MB.

EN: Converts kitchen measures between volume (cup, tbsp, tsp, ml, l, fl_oz, metric cup) and weight (g, kg, oz, lb) for common ingredients using typical densities. Results are approximate. When: a quantity has to be converted between units with exact definitional factors. Not for: converting volume between units (convert-volume). Side effects: none (read-only, no network access, no stored state). Deterministic: the same input gives the same output. [EN completo / full EN: inputSchema.description]

Input Schema

Name	Required	Description	Default
`to`	Yes	Target measure (required; one of: cup, tbsp, tsp, ml, l, fl_oz, cup_metric, g, kg, oz, lb).
`from`	Yes	Source measure (required; one of: cup, tbsp, tsp, ml, l, fl_oz, cup_metric, g, kg, oz, lb).
`value`	Yes	Amount (number; required; min 0).
`ingredient`	No	Ingredient (needed for volume↔weight) (optional; one of: water, milk, flour, sugar, brown_sugar, powdered_sugar, butter, oil, honey, rice, oats, cocoa, salt, cornstarch, …; default "water").	water

Output Schema

Name	Required	Description
`to`	No
`from`	No
`value`	No	any JSON value
`result`	No	any JSON value
`ingredient`	No
`approximate`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedNov 2, 2026
- addedInput schema / properties / from / examples
```
Added value: +[
+  "cup"
+]
```
- addedInput schema / properties / to / examples
```
Added value: +[
+  "g"
+]
```
- addedInput schema / properties / value / examples
```
Added value: +[
+  1
+]
```

Changed1 schema field changedNov 1, 2026

addedInput schema / description

Added value: +"EN: Converts kitchen measures between volume (cup, tbsp, tsp, ml, l, fl_oz, metric cup) and weight (g, kg, oz, lb) for common ingredients using typical densities. Results are approximate. When: a quantity has to be converted between units with exact definitional factors. Not for: converting volume between units (convert-volume). Side effects: none (read-only, no network access, no stored state). Deterministic: the same input gives the same output. Limits: JSON input up to 64 KB, 1 s per call, result up to 1 MB."

First observedNov 1, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world behavior. The description adds useful non-annotation context: typical densities, approximate results, determinism, and size/time limits. It does not contradict the annotations.

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 core Spanish description is front-loaded and structured with Cuándo/No para/Efectos/Límites labels. However, the full English restatement duplicates nearly all content and makes the definition unnecessarily long; 'exact definitional factors' also adds ambiguity.

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?

The tool has an output schema, complete parameter schema, and rich annotations. The description covers purpose, sibling exclusion, determinism, side effects, and operational limits, so an agent has enough to invoke it correctly. The only gap is that the exact-factor wording vs approximate results could confuse expectations.

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 the schema already documents value, from, to, and ingredient, including the ingredient default and volume-to-weight need. The description adds only broad context that common ingredients use typical densities and results are approximate, which is useful but not substantial beyond the schema.

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?

The description states a specific verb and resource: converting kitchen measures between volume and weight for common ingredients. It explicitly distinguishes this from the sibling convert-volume, which handles volume-to-volume conversion, so an agent can route correctly without opening schemas.

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?

It gives a clear 'Cuándo'/'When' condition and an explicit 'No para' pointing to convert-volume as the alternative. The guidance is slightly weakened by the phrase 'factores de definición exactos', which sits awkwardly with the stated approximate density-based results.

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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