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Burs-IA Utils

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Dividir oraciones en español

es-sentence-split
Read-onlyIdempotent

Divide un texto en español en oraciones, considerando ¿…? y ¡…!, puntos suspensivos, decimales y miles (3.5, 1.000), iniciales (J. R.) y abreviaturas comunes (Sr., Dra., Uds., pág., núm., Cra., EE. UU., S.A.S.). Devuelve posiciones. Cuándo: hay que tratar texto, números o fechas en español según las reglas escritas del idioma y no por aproximación. No para: dividir un texto en fragmentos con solapamiento para recuperación (rag-chunk). 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: Splits Spanish text into sentences, aware of ¿…? and ¡…!, ellipses, decimals and thousands (3.5, 1.000), initials (J. R.) and common abbreviations (Sr., Dra., Uds., pág., núm., Cra., EE. UU., S.A.S.). Returns offsets. [EN completo / full EN: inputSchema.description]

Input Schema

NameRequiredDescriptionDefault
textYesSpanish text (string; required).

Output Schema

NameRequiredDescriptionDefault
countNo
sentencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / text / examples
      Added value: +[
+  "¿Vienes mañana? El Sr. Pérez llega a las 3.30. ¡Qué bien!"
+]
  2. Changed1 schema field changed
    • addedInput schema / description
      Added value: +"EN: Splits Spanish text into sentences, aware of ¿…? and ¡…!, ellipses, decimals and thousands (3.5, 1.000), initials (J. R.) and common abbreviations (Sr., Dra., Uds., pág., núm., Cra., EE. UU., S.A.S.). Returns offsets. When: Spanish text, numbers or dates have to be handled by the written rules of Spanish instead of by approximation. Not for: splitting text into overlapping chunks for retrieval (rag-chunk). 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."
  3. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered. The description adds genuinely new behavior: explicit limits (64 KB input, 1 s per call, 1 MB result) and determinism. It does not describe offset format details, but with annotations and an output schema present, this is solid added context.

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?

The core purpose is front-loaded and the labeled sections (Cuándo/No para/Efectos/Límites) are scannable and earn their place. Some duplication from the ES/EN mirroring makes it slightly longer than strictly necessary.

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

Completeness5/5

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

For a single-parameter, read-only splitter with an output schema, the description covers purpose, edge cases, when/when-not, side effects, determinism and hard limits. Return values ('Devuelve posiciones') are noted and detailed by the output schema, so nothing an agent needs is missing.

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?

There is only one parameter and schema description coverage is 100%, with examples and maxLength already in the schema. The description adds no syntax or format detail for the text parameter beyond what the schema provides, so the baseline 3 applies.

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?

States a specific verb and resource (split Spanish text into sentences) and enumerates the exact edge cases handled: ¿…?/¡…!, ellipses, decimals/thousands, initials, abbreviations. It also names the sibling it is not (rag-chunk), so an agent can distinguish it without opening the schema.

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

Usage Guidelines5/5

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

Explicit 'Cuándo' states the condition for use (handling Spanish text/numbers/dates by written language rules rather than approximation) and 'No para' names the alternative tool (rag-chunk) for the overlapping case. Nothing is left to inference.

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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