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Burs-IA Utils

by io.github.soyeladice-svg
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Quitar caracteres invisibles

text-invisible-strip
Read-onlyIdempotent

Elimina caracteres invisibles; opcionalmente conserva ZWJ y selectores de variación para no romper emojis. Cuándo: hay que transformar, comparar o medir un texto con exactitud y no por aproximación. No para: detectar caracteres invisibles (text-invisible-scan). 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: Removes zero-width, bidi-control, Unicode tag and other invisible format characters; optionally keeps ZWJ (U+200D) and variation selectors so emoji sequences survive. When: text has to be transformed, compared or measured exactly instead of approximated. Not for: finding zero-width, bidi-control, Unicode tag and other invisible characters (text-invisible-scan). 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
textYesText (string; required).
keep_emoji_joinersNoKeep U+200D and variation selectors (boolean; optional; default true).

Output Schema

NameRequiredDescriptionDefault
textNo
removedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / text / examples
      Added value: +[
+  "he​l‮lo"
+]
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the hints provided in annotations, the description details crucial behavioral traits: 'Deterministic' behavior, 'no network access', 'no stored state', and defines concrete operational limits for input and output size.

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 definition is expertly structured, front-loading the function, followed by context (When/Not For), behavioral limits (Side effects/Limits), and technical constraints (Deterministic).

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?

The definition is fully comprehensive. Given the detailed schema and annotations, it covers all necessary logic for correct selection and invocation, including operational boundaries and relationship with sibling tools.

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?

Although schema coverage is 100%, the description adds critical context by explaining that 'keep_emoji_joiners' is used 'so emoji sequences survive,' which gives semantic depth to the optional boolean parameter that the schema description alone does not provide.

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 is immediately clear, specifying that the tool eliminates zero-width, bidi-control, Unicode tag, and other invisible format characters using a specific action verb ('Removes').

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?

The usage guidelines are extremely precise, stating that it should be used 'When' text needs exact comparison or measurement, and explicitly stating what it should *not* be used for, referencing the sibling tool (text-invisible-scan).

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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