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Read the dominant colours of an image

image_dominant_colors

Call this tool to read the colours covering most of an image, as hex codes with each one's pixel share. Sampled from a 200 px copy, so cost is fixed. Read-only. Free gives the top 3; Pro up to 16.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesName of an image uploaded with image_upload, or one this server wrote earlier
countNoHow many colours to report, default 5

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior1/5

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

The description states 'Read-only,' but the annotations set readOnlyHint to false, which directly contradicts the description. The additional details about sampling from a 200 px copy and fixed cost are useful, but under the contradiction rule this dimension scores 1. Annotation Contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded with the primary purpose, and every sentence adds useful information: output format, sampling/cost behavior, read-only nature, and plan limits. No filler or redundancy.

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?

For a simple analysis tool with 100% schema coverage and no output schema, the description covers the key things an agent needs: what it returns, how it samples, cost behavior, and count limits. The only completeness gap is the conflicting read-only claim, already penalized under behavioral transparency.

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?

Schema coverage is 100%, so baseline is 3. The description adds meaningful parameter behavior beyond the schema: 'Free gives the top 3; Pro up to 16' clarifies how the count parameter behaves by plan, and the path's source is already clear from the schema. This extra plan-dependent nuance raises it to 4.

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?

The description opens with a clear, specific action: 'read the colours covering most of an image' and specifies the output format as hex codes with pixel share. This clearly distinguishes it from sibling tools like image_info, image_resize, or image_compress.

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?

It explicitly says when to call the tool ('Call this tool to read...') and gives useful context about cost and plan limits. It does not name an alternative tool or state when not to use it, but among the image manipulation siblings the intended use is clear.

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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