rd_kcentroidDownscale images while preserving color palettes using k-means centroid selection, with an option to re-add outlines.
K-Centroid Resize: downscale images with k-means palette preservation (centroids = target colors), optionally re-adding an outline.
| Name | Required | Description | Default |
|---|---|---|---|
| width | No | ||
| height | No | ||
| outline | No | ||
| centroids | No | ||
| image_paths | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains the algorithmic approach and the optional outline behavior, but does not mention side effects, file mutation, output format, or constraints beyond what the schema provides.
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 a single tight sentence with no filler and the key method is front-loaded. Slight redundancy with the tool name 'K-Centroid Resize' keeps it from being perfect.
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?
For a tool with five parameters and an output schema, the description covers the core algorithm but omits important invocation context like whether input files are modified in place, what output is produced, and when this method is preferable to similar tools. It is minimally viable but not rich.
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 0%, so the description must compensate. It usefully clarifies 'centroids = target colors' and names the outline option, but does not elaborate on width/height semantics or the image_paths parameter, which remain dependent on naming conventions.
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 identifies the action as downscaling images and specifies the unique k-means palette preservation method. It distinguishes this tool from generic resize operations like rd_neural_resize or ase_scale_sprite, though it does not explicitly name those alternatives.
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?
No guidance is provided on when to use this tool versus the many similar image-resizing or palette-related sibling tools. The intended context must be inferred from the description and parameter names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.