UI Preset MCP Server

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, and idempotentHint=true, covering safety and idempotency. The description adds valuable context beyond this: it explains the tool's generative nature (suggestions based on description) and output options (preset_id, tokens, full with reasoning), which are not captured in annotations. No contradictions exist.

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 front-loaded with the core purpose in the first sentence, followed by a structured 'Args' section with clear bullet points and examples. Every sentence adds value without redundancy, and the 'Returns' statement succinctly summarizes the output. It is efficiently sized for the tool's complexity.

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 (2 parameters, 100% schema coverage, no output schema), the description is largely complete. It covers purpose, parameters with examples, and output behavior. However, it lacks details on potential limitations (e.g., accuracy of suggestions, handling of ambiguous descriptions) or error cases, which could enhance completeness.

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 parameters. The description adds meaning by providing concrete examples for 'description' (e.g., 'dark hacker terminal') and clarifying the purpose of 'output_format' options (e.g., 'full' includes 'category info, and reasoning'), enhancing understanding beyond schema definitions.

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: 'Get a style preset and token override suggestions based on a natural-language aesthetic description.' It specifies the verb ('Get'), resources ('style preset and token override suggestions'), and input mechanism ('natural-language aesthetic description'), distinguishing it from siblings like 'list_presets' (which lists) or 'load_preset' (which loads a specific preset).

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 implies usage context by mentioning 'natural-language aesthetic description' and provides examples (e.g., 'dark hacker terminal'), but does not explicitly state when to use this tool versus alternatives like 'list_presets' or 'generate_tokens'. It offers clear guidance on the input but lacks sibling differentiation or exclusions.

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