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halo-light

halo-light

set_color_rgb

Idempotent

Set a specific light's color using RGB values from 0 to 255, letting AI assistants control Philips Hue lights by target light ID or name.

Instructions

Set a light's color from RGB components (0-255).

Input Schema

NameRequiredDescriptionDefault
redYes
blueYes
greenYes
light_idNo
light_nameNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnly=false, idempotent=true, destructive=false, and closed-world, so the safety profile is covered. The description adds one genuinely useful behavioral detail the annotations lack: the valid component range (0-255), which is absent from the schema. It says nothing about targeting behavior, invalid-value handling, or what happens when both or neither identifier is supplied.

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?

A single front-loaded sentence with no filler; the range constraint is attached directly to the parameter it governs. It is efficient, though the terseness comes at the cost of the targeting and alternative-selection information noted above.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

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, but the input side is under-specified for a 5-parameter tool at 0% schema coverage. An agent cannot tell how to identify the target light, whether the identifiers are mutually exclusive or which wins, or what the empty-string defaults imply.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 5 parameters, so the description carries the full burden and only partly meets it: it documents the red/green/blue range but not their individual meaning. The two optional targeting parameters (light_id, light_name) and their interaction are entirely unaddressed in both schema and description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ("Set a light's color") plus the input mode (RGB components 0-255), which implicitly separates it from set_color_xy and set_color_temperature. It never names those siblings explicitly, so the agent must infer the distinction from the parameter vocabulary alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance: nothing says to prefer set_color_xy for gamut-accurate colors or set_color for named colors. It also gives no hint about choosing between light_id and light_name, so targeting must be inferred entirely from the schema.

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