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Simular daltonismo

color-blindness-simulate
Read-onlyIdempotent

Simula cómo se ve un color con protanopía, deuteranopía, tritanopía o acromatopsia. Cuándo: hay que calcular con exactitud colores, contrastes o paletas, p. ej. para revisar accesibilidad. No para: convertir colores CSS (color-convert). 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: Simulates how a color appears with protanopia, deuteranopia, tritanopia (Machado et al. 2009, severity 1) or achromatopsia, to check palettes for color-blind users. When: color values, contrast or palettes have to be computed exactly, e.g. for accessibility checks. Not for: parsing any common CSS color (color-convert). 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
colorYesCSS color: hex, rgb(), hsl(), hwb(), oklch(), oklab() or a named color (string; required; up to 100 chars).

Output Schema

NameRequiredDescriptionDefault
protanopiaNo
tritanopiaNo
deuteranopiaNo
achromatopsiaNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / color / examples
      Added value: +[
      +  "#ff0000"
      +]
  2. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/closed-world, and the description still adds substantive beyond-annotation facts: no network access, no stored state, deterministic output, plus concrete limits (64 KB JSON input, 1 s per call, 1 MB result). This is exactly the rate/limit and side-effect detail an agent needs and cannot infer from the annotation block.

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?

Each language block is tightly front-loaded with purpose, then When/Not-for/Side effects/Determinism/Limits in a consistent scannable order. The cost is that the whole definition is duplicated verbatim in Spanish and English, roughly doubling length with no new information.

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?

With an output schema present, the description needn't describe return values, and annotations plus the explicit limits, determinism and no-side-effects notes cover everything else. Nothing material for a correct invocation 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?

Schema coverage is 100% and the single parameter documents accepted CSS color formats, so the schema already carries the semantics. The description adds only an indirect constraint (JSON payload up to 64 KB) but nothing about the color format, mixing model or severity handling. 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 (simulate how a color appears) plus the exact deficit variants covered (protanopia, deuteranopia, tritanopia, achromatopsia) and the underlying model. It is immediately distinguishable from neighbors like color-convert, color-contrast or color-delta-e.

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 'When' clause (exact computation of colors, contrast or palettes, e.g. accessibility checks) and an explicit 'Not for' clause naming the sibling color-convert that handles CSS color parsing. Both the selection and exclusion conditions are stated.

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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