Burs-IA Utils

Nombre CSS de color más cercano

color-name-nearest

Read-onlyIdempotent

Encuentra el nombre de color CSS más cercano a un color dado (distancia OKLab). 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: Finds the closest of the 148 CSS named colors to a given color (by OKLab distance), with the distance, and whether it is an exact match. 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

Name	Required	Description	Default
`top`	No	How many candidates (integer; optional; default 1; min 1; max 10).
`color`	Yes	CSS color: hex, rgb(), hsl(), hwb(), oklch(), oklab() or a named color (string; required; up to 100 chars).

Output Schema

Name	Required	Description	Default
`exact`	No
`matches`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 2, 2026
- addedInput schema / properties / color / examples
```
Added value: +[
+  "#ff6348"
+]
```
First observedNov 1, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive and closed-world, so restating 'no side effects' adds little. However, the description adds genuinely new behavioral context beyond annotations: deterministic output, and concrete limits (64 KB input, 1 s per call, 1 MB result). Return-shape detail is deferred to the output 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?

Well front-loaded with labelled sections (When / Not for / Side effects / Limits) that are easy to scan. The only waste is the bilingual duplication, which doubles length but does not add noise for a Spanish/English audience.

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?

An output schema exists so return values need no explanation. With purpose, exclusions, determinism and limits all stated, nothing an agent needs to invoke this correctly 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% with both parameters fully documented, so the baseline is 3. The description mentions the input is a color value but does not clarify the 'top' parameter (candidate count) or add meaning beyond the schema.

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 ('Finds the closest of the 148 CSS named colors to a given color') and specifies the OKLab distance metric plus exact-match reporting. It explicitly names the sibling it is not (color-convert), so an agent can distinguish the two without opening either 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?

Provides an explicit 'When' clause (exact color/contrast/palette computation, accessibility checks) and a 'Not for' clause pointing to color-convert as the alternative. The routing decision is fully specified.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Burs-IA Utils tools Inspect

Try in Browser

Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?