UI Preset MCP Server

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

The description adds context beyond annotations by detailing the return structure (e.g., 'hsl', 'semantic', 'shades'), which is valuable since annotations only cover read-only, non-destructive, and idempotent traits. It doesn't contradict annotations, which correctly indicate a safe read operation, and provides useful output information not in the 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 well-structured and front-loaded with the core purpose, followed by organized sections for arguments and returns, and ends with usage guidance. Every sentence earns its place without redundancy, making it efficient and easy to parse.

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?

Given the tool's moderate complexity, rich annotations, and 100% schema coverage, the description is complete enough. It explains the purpose, parameters, return values, and usage context, compensating for the lack of an output schema by detailing the return structure, which ensures the agent can effectively use the tool.

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?

The description includes an 'Args' section that lists parameters with brief explanations, but since schema description coverage is 100%, the schema already provides detailed descriptions for each parameter. The description adds minimal value beyond the schema, such as example values for 'seed_color', but doesn't significantly enhance parameter understanding, meeting the baseline of 3 for high schema coverage.

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 purpose with specific verbs ('generate a harmonious color palette') and resources ('from a seed hex color using color theory'), distinguishing it from siblings like 'generate_tokens' or 'suggest_style' by focusing on color palette generation rather than tokens or style suggestions.

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 explicitly provides usage guidance by stating 'Use the result to populate apply_token_overrides or scaffold_preset,' naming specific sibling tools as alternatives for downstream actions, which helps the agent understand when to use this tool versus others in the workflow.

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