Extract dominant color palette from an image. Returns hex/RGB/HSL colors with percentages, CSS names, and complementary colors. Great for design systems, mood boards, and color matching. FREE. (FREE)
| Name | Required | Description | Default |
|---|---|---|---|
| image | Yes | Base64-encoded PNG/JPEG image | |
| format | No | Color format in output | hex |
| num_colors | No | Number of colors to extract (3-12) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable behavioral details beyond that by specifying the output: 'hex/RGB/HSL colors with percentages, CSS names, and complementary colors.' It also mentions 'FREE' as a pricing/safety signal. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact overall, but 'FREE. (FREE)' is redundant and wastes space, violating the principle that every sentence should earn its place. The rest is front-loaded with the core purpose and output details, but the repetition lowers the score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description appropriately explains the return values ('hex/RGB/HSL colors with percentages, CSS names, and complementary colors'). It covers the core functionality and use cases. Though it doesn't specify the exact JSON structure, the level of detail is sufficient for a moderately complex tool with good annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters (image, format, num_colors). The description mentions hex/RGB/HSL which aligns with the format enum, but adds no new meaning beyond the schema. Baseline of 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Extract dominant color palette from an image.' This distinguishes it from sibling tools like convert_color_profile or resize_image, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear application contexts: 'Great for design systems, mood boards, and color matching.' It implies when to use the tool, though it does not explicitly state when not to use it or mention alternatives. This is solid guidance but lacks explicit exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes, but there is some overlap between get_artwork and get_artwork_oracle, which both retrieve artwork metadata with different detail levels, potentially causing confusion. Other tools like enrich_metadata and infuse_metadata also have related but distinct functions, but descriptions help clarify differences.
Tool names generally follow a consistent verb_noun pattern (e.g., check_balance, delete_asset, resize_image), with minor deviations like mockup_image (noun_verb) and get_artwork_oracle (longer compound name). Overall, the naming is readable and predictable, though not perfectly uniform.
With 27 tools, the count is borderline high for a single server, as it covers a broad range of functionalities from artwork retrieval to image processing and compliance. While each tool seems useful, the scope feels heavy and could overwhelm agents, suggesting it might be better split into more focused servers.
The tool set provides comprehensive coverage for digital asset management, artwork analysis, and image processing, including CRUD operations (save_asset, get_asset, list_assets, delete_asset), metadata enrichment, compliance, and various image utilities. No obvious gaps are present for the stated domain.