Page Design Guide MCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns guidance but doesn't cover critical traits: it doesn't specify if this is static or dynamic data, whether it requires authentication, potential rate limits, or the format of the return (e.g., structured JSON, text). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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, efficient sentence: 'Returns font hierarchy scales, font pairings, and readability best practices.' It is front-loaded with the verb 'Returns' and lists key outputs without unnecessary words. Every part of the sentence adds value by specifying the tool's scope, making it appropriately sized and well-structured.

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 complexity (simple retrieval with no parameters) and lack of annotations/output schema, the description is minimally adequate. It states what is returned but doesn't cover behavioral aspects like data freshness, source, or format. Without an output schema, it should ideally hint at the return structure, but the description focuses only on content, leaving gaps in completeness for practical use.

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 tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, but it does imply the scope of the output (font hierarchy, pairings, readability). This aligns with the lack of inputs, making a baseline score of 4 appropriate as it compensates by clarifying the output content.

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 outputs: 'Returns font hierarchy scales, font pairings, and readability best practices.' It uses a precise verb ('Returns') and lists concrete resources, distinguishing it from siblings like 'get_color_guidance' or 'get_layout_patterns' by focusing on typography. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_accessibility_guidance' might overlap with readability).

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., for design reviews or UI development), or exclusions. With multiple sibling tools like 'get_holistic_design_review' or 'get_section_guidance', there's no indication of when typography guidance is preferred over broader or more specific resources.

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