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Temperatura de color a RGB

color-temperature
Read-onlyIdempotent

Aproxima el color sRGB de una fuente de luz a una temperatura de 1.000 K a 40.000 K. Cuándo: hay que calcular con exactitud colores, contrastes o paletas, p. ej. para revisar accesibilidad. No para: ajustar un color en OKLCH (color-adjust). 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: Approximates the sRGB color of a black-body light source at a temperature from 1,000 K to 40,000 K (Tanner Helland fit), e.g. 2700 K warm white or 6500 K daylight. When: color values, contrast or palettes have to be computed exactly, e.g. for accessibility checks. Not for: adjusting a color in OKLCH (color-adjust). 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
kelvinYesTemperature in kelvin (number; required; min 1000; max 40000).

Output Schema

NameRequiredDescriptionDefault
hexNo
rgbNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / kelvin / examples
      Added value: +[
      +  6600
      +]
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

The annotations already declare readOnlyHint, openWorldHint=false, idempotentHint and destructiveHint=false, so restating "read-only, no network, no state, deterministic" is largely redundant. What the description genuinely adds beyond structured data are the operational limits — 64 KB JSON input, 1 s per call, 1 MB result — which are not encoded in any annotation or schema.

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 block is tight and front-loaded: capability, then When / Not for, then side effects, then limits. The only cost is that the entire text is duplicated verbatim in Spanish and English, doubling length without adding information for a reader who parses both.

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, deterministic, read-only conversion with a fully documented schema, a declared output schema, and complete annotations, nothing an agent needs is missing — routing, semantics, limits and determinism are all covered.

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?

With one parameter at 100% schema coverage, the baseline is 3; the description goes slightly beyond by framing kelvin as a black-body light-source temperature and tying it to real-world reference values (2700 K warm white, 6500 K daylight), which helps an agent pick a sensible input rather than just a bounded number.

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?

"Approximates the sRGB color of a black-body light source at a temperature from 1,000 K to 40,000 K" states a concrete verb, a precise resource, and an explicit domain range, plus the implementation fit (Tanner Helland) and concrete examples (2700 K warm white, 6500 K daylight). It is instantly distinguishable from color-convert, color-mix and color-adjust.

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?

Contains explicit "When:" guidance (computing exact color values, contrast, palettes, accessibility checks) and an explicit "Not for:" that names the correct alternative sibling (color-adjust for OKLCH). Both the positive and negative routing conditions are stated rather than implied.

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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