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RoomLab.app

Wall Colors

visualize_wall_colors
Destructive

Use this when the user wants to compare paint colors on the walls of the same room. It returns a nine-color comparison. Color preferences are optional; use RoomLab’s balanced default palette when the user did not specify colors.

Input Schema

NameRequiredDescriptionDefault
imageNoThe room image attached by the user. Do not ask the user for file metadata.
colorsNoOptional nine paint colors in grid order. Omit to use the same nine defaults shown in the workspace.
image_urlNoA link or inline copy of the room image supplied by the client.
additional_instructionsNoOptional user preferences stated in natural language. Do not ask for this when the request is already clear.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

The description adds useful behavior beyond the annotations: it returns nine variants rather than one, and it silently falls back to a balanced default palette when the user gives no colors. However, it never addresses the destructiveHint=true annotation — it doesn't say whether the original room image is preserved or overwritten, nor anything about cost/latency for an open-world generation call.

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?

Three short sentences with the trigger condition front-loaded and no filler. The sentence about optional color preferences largely repeats the schema's own wording, costing a little space.

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

Completeness4/5

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 needn't be explained, and the description still summarizes the nine-color result. For a generation tool flagged destructive and open-world, the main remaining gap is not stating whether the source image is modified or preserved.

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 description coverage is 100% and the nested image/base64 variants are heavily documented in the schema itself, so the schema does the heavy lifting. The description only restates that colors are optional and defaulted, adding no detail about the color array format, ordering, or the additional_instructions parameter.

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 gives a specific verb ('compare') and resource ('paint colors on the walls of the same room') and states the output shape ('a nine-color comparison'), which is unique among the sibling tools that instead replace materials, furniture, or styles. It stops short of naming the closest alternative (e.g. replace_material) to sharpen the boundary.

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

Usage Guidelines4/5

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

'Use this when the user wants to compare paint colors on the walls of the same room' gives a clear triggering condition, and the note about defaulting to RoomLab's palette covers the underspecified-request case. No alternative tool or exclusion is named, so the agent must infer when a different rendering tool is better.

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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