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Agregar sangría

text-indent
Read-onlyIdempotent

Antepone un prefijo a cada línea (o solo a las no vacías). Cuándo: hay que transformar, comparar o medir un texto con exactitud y no por aproximación. No para: eliminar la sangría común de todas las líneas no vacías (text-dedent). 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: Prefixes every line (or only non-blank lines) with a given string, e.g. spaces, tabs or "> ". When: text has to be transformed, compared or measured exactly instead of approximated. Not for: removing the common leading whitespace from every non-blank line (text-dedent). 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.

Input Schema

NameRequiredDescriptionDefault
textYesInput text (string; required).
prefixNoPrefix (string; optional; default " "; up to 64 chars).
skip_blankNoLeave blank lines untouched (boolean; optional; default true).

Output Schema

NameRequiredDescriptionDefault
textNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / text / examples
      Added value: +[
      +  "a\n\nb"
      +]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint=false, idempotentHint and destructiveHint=false, so the "no side effects / deterministic" sentences largely restate structured data. The description does add genuinely new behavioral data: per-call resource limits (64 KB input, 1 s, 1 MB result). Note the stated 64 KB input cap sits below the schema's 262144-char maxLength, a soft inconsistency worth flagging but not an annotation contradiction.

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?

Front-loaded with the verb and scope, then clearly labeled sections (Cuándo / No para / Efectos / Determinista / Límites) that scan well. The full bilingual duplication roughly doubles length, which is defensible for discoverability but is not maximally economical.

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?

With an output schema present, return values need no explanation, and the description covers scope, alternative, safety, determinism and limits. Only minor gaps remain, e.g. how trailing newlines or an empty final line are treated.

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?

Schema description coverage is 100%, so baseline is 3; the description goes slightly beyond by giving concrete prefix examples (spaces, tabs, "> ") and by making the skip_blank toggle explicit in prose ("o solo a las no vacías"). It does not explain defaults, which the schema already carries.

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 ("Antepone un prefijo a cada línea") with the exact scope qualifier "o solo a las no vacías", and explicitly names the opposite operation text-dedent. An agent can distinguish this from text-dedent and text-pad without reading any 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?

Has explicit "Cuándo" (when to use: exact transformation/comparison/measurement instead of approximation) and "No para" (when not: use text-dedent to strip common leading whitespace), naming the alternative sibling by name. 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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