Page Design Guide MCP

Server Quality Checklist

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Latest release: v1.0.10
Disambiguation4/5
Most tools have distinct purposes targeting specific design aspects like accessibility, color, layout, and typography. However, there is some overlap between get_color_guidance and get_modern_palettes, which could cause confusion as both deal with color-related guidance, though the former is more general and the latter focuses on trending palettes.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using 'get_' followed by a descriptive noun phrase (e.g., get_accessibility_guidance, get_animation_guidance). This uniformity makes the tool set predictable and easy to navigate for an agent.
Tool Count5/5
With 12 tools, the count is well-scoped for a design guide server, covering a comprehensive range of topics from principles to specific components. Each tool appears to serve a distinct role in the domain without being excessive or insufficient.
Completeness5/5
The tool set provides complete coverage for a page design guide, including core principles, specific elements (color, typography, components), layout patterns, responsive design, and holistic reviews. There are no obvious gaps; agents can access guidance for all major design aspects without dead ends.
Average 3.2/5 across 12 of 12 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 mentions returning 'detailed design specs' but doesn't specify format, size, or structure of the output. It also doesn't cover error handling, rate limits, or authentication needs. The description is vague about what 'best practices' entail, leaving behavioral traits unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Returns detailed design specs for UI components') and adds specific examples and context without waste. Every word earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that returns 'detailed design specs.' It lacks information on output format, data structure, or examples, which are crucial for an AI agent to understand what to expect. The complexity of design specs warrants more detail than provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'component' fully documented in the schema (type, description, enum values, optionality). The description adds no additional parameter semantics beyond what the schema provides, such as examples of output for each component type. Baseline score 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Returns detailed design specs for UI components' with specific examples (buttons, cards, forms, navigation) and mentions 'modern 2026 best practices.' It distinguishes itself from siblings by focusing on UI components rather than accessibility, animation, color, etc. However, it doesn't explicitly contrast with all siblings (e.g., 'get_section_guidance' might overlap).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, or exclusions, and doesn't reference sibling tools like 'get_layout_patterns' or 'get_section_guidance' that might be relevant for UI design. Usage is implied by the purpose but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool returns advice but does not disclose behavioral traits such as whether it's a read-only operation, if there are rate limits, authentication needs, or what format the advice is in (e.g., text, structured data). This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. It could be slightly more structured by explicitly stating the parameter's role, but it avoids unnecessary details and wastes no words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It does not explain what the returned advice entails (e.g., format, depth), behavioral aspects, or how it differs from siblings. For a tool with no structured support, more context is needed to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting the optional 'section' parameter with an enum list. The description adds minimal value beyond the schema by mentioning examples (hero, footer, features), which are subsets of the enum, but does not explain semantics like what 'Returns all if empty' means in practice. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 a specific verb ('Returns') and resource ('structure and design advice for common page sections'), and it lists examples of sections (hero, footer, features). However, it does not explicitly differentiate from sibling tools like 'get_component_guidance' or 'get_layout_patterns', which might overlap in scope, so it falls short of a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 does not mention sibling tools or contexts where other guidance tools might be more appropriate, leaving the agent to infer usage based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While it states the tool 'returns' something (implying a read operation), it doesn't address important behavioral aspects like whether this requires authentication, if there are rate limits, what format the checklist uses, or whether the results are cached. For a tool with zero annotation coverage, this minimal description leaves significant behavioral questions unanswered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise - a single sentence that directly states what the tool does without any unnecessary words. Every word earns its place: 'Returns' (action), 'comprehensive checklist' (output type), 'all design categories' (scope), and 'to review a user's concept' (purpose). The structure is front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the context of 11 sibling tools providing various design guidance, this description is incomplete. It doesn't explain how this 'holistic' tool relates to the specific guidance tools, what makes it 'comprehensive,' or what format the checklist returns. With no output schema and no annotations, the description should provide more context about the return value and behavioral characteristics to compensate for the missing structured information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema description coverage is 100% (though trivial since there are no parameters). The description appropriately doesn't waste space discussing nonexistent parameters. A baseline of 4 is appropriate for zero-parameter tools where the schema fully documents the empty parameter set.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 a specific verb ('Returns') and resource ('comprehensive checklist of all design categories'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish this tool from its siblings, which all provide various types of design guidance. A perfect score would require clarifying how this 'holistic review' differs from the more specific guidance tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 its many siblings. With 11 other design guidance tools available, the agent receives no indication whether this should be used first, last, or instead of specific tools like 'get_design_principles' or 'get_component_guidance'. The description implies a 'comprehensive' scope but doesn't specify relationships to the more focused tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 information, implying a read-only operation, but doesn't cover aspects like data freshness, source credibility, rate limits, or error handling. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Returns current visual design trends and what trends to avoid.' It's front-loaded with the core purpose and avoids unnecessary words. However, it could be slightly more structured by explicitly mentioning the lack of parameters or output format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity is low (0 parameters, no annotations, no output schema), the description is minimally adequate. It states what the tool does but lacks details on behavior, usage context, or output format. With no output schema, the description doesn't explain return values, which is a gap, but the simplicity of the tool keeps it from being completely inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, but since there are no parameters, this is acceptable. Baseline is 4 for 0 parameters, as the schema fully covers the lack of inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Returns current visual design trends and what trends to avoid.' It specifies the verb 'returns' and the resource 'visual design trends' with additional context about 'what trends to avoid.' However, it doesn't explicitly differentiate from siblings like 'get_design_principles' or 'get_layout_patterns,' which might overlap in design guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 any context, prerequisites, or exclusions, and with multiple sibling tools like 'get_design_principles' and 'get_layout_patterns' that could be related, the lack of differentiation leaves the agent without clear usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Returns'), but lacks details on permissions, rate limits, response format, or whether the guidance is static or dynamic. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded with the core purpose, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It covers the basic purpose but lacks behavioral context and usage guidelines. For a read-only tool with no structured output documentation, more detail on response format would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to compensate for parameter documentation, and it appropriately doesn't mention parameters. Baseline 4 is appropriate for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 a specific verb ('Returns') and resource ('a11y standards'), specifying the topics covered (contrast, focus states, semantic HTML). It distinguishes from some siblings like 'get_color_guidance' by mentioning contrast, but doesn't fully differentiate from all potential overlaps like 'get_component_guidance' which might include accessibility aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. The description doesn't mention when-not scenarios or refer to sibling tools like 'get_holistic_design_review' that might cover broader accessibility topics, leaving usage context implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns best practices, implying a read-only operation, but does not cover aspects like response format, potential rate limits, or error handling. This leaves gaps in understanding how the tool behaves beyond its basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It explains what the tool does but lacks details on behavioral traits or usage context, which could be helpful for an agent in a guidance-focused server with many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter information is needed. The description appropriately does not discuss parameters, and since there are none, it meets the baseline of 4 for not introducing confusion or redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 a specific verb ('Returns') and resource ('best practices for UI animation timing, easing, and purpose'), making it easy to understand what it does. However, it does not explicitly differentiate from sibling tools like 'get_accessibility_guidance' or 'get_layout_patterns', which reduces the score from a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, such as other guidance tools in the sibling list. There is no mention of context, prerequisites, or exclusions, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns information, implying a read-only operation, but lacks details on response format, potential rate limits, or any side effects. This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key action ('Returns') and lists the three main outputs without unnecessary words. Every part of the sentence contributes directly to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple read operation with no parameters) and lack of annotations and output schema, the description is minimally adequate. It states what is returned but does not cover behavioral aspects like format or limitations, leaving gaps that could hinder effective use by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 no parameter documentation is needed. The description does not add parameter details, which is appropriate, but it could hint at optional filters or scoping if relevant, though not required for a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 the verb 'Returns' and specifies the resources: 'color psychology, color scheme types, and modern palette examples.' It distinguishes itself from siblings like 'get_modern_palettes' by including broader color guidance, but could be more explicit about the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives. For example, it does not clarify when to choose this over 'get_modern_palettes' or 'get_holistic_design_review,' leaving the agent to infer usage from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 that the tool 'retrieves' principles, implying a read-only operation, but doesn't specify any behavioral traits like whether it requires authentication, has rate limits, returns structured data, or if the retrieval is cached. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key action ('Retrieves core UI/UX principles') and adds clarifying details ('hierarchy, whitespace, contrast') and purpose ('to ensure visual quality'). Every part earns its place with no wasted words, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains what the tool does but lacks behavioral details (e.g., response format, error handling) and usage guidelines relative to siblings. Without annotations or an output schema, the description should do more to compensate, but it only meets the minimum viable level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so the schema fully documents that no inputs are required. The description adds no parameter information, which is appropriate here. Since there are no parameters, the baseline score is 4, as the description doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 a specific verb ('Retrieves') and resource ('core UI/UX principles'), and it lists examples of what those principles include (hierarchy, whitespace, contrast). However, it doesn't explicitly differentiate this tool from its siblings like 'get_layout_patterns' or 'get_holistic_design_review', which might also relate to design principles or guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 its many siblings, such as 'get_accessibility_guidance' or 'get_color_guidance'. It mentions the purpose ('to ensure visual quality'), but this is vague and doesn't help an agent decide between alternatives. There are no explicit when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 data, implying a read-only operation, but doesn't address potential behavioral aspects like rate limits, authentication needs, data freshness, or error handling. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the core functionality: 'Returns trending 2026 color palette combinations with specific hex codes and usage examples.' It is front-loaded with the main action and includes key details without unnecessary elaboration, making it highly concise and effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple read operation with no parameters) and lack of annotations or output schema, the description is minimally adequate. It specifies what is returned but doesn't cover behavioral aspects or usage context. For a tool with no structured data beyond the schema, it provides basic completeness but lacks depth for optimal agent guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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, and it appropriately avoids discussing inputs. A baseline score of 4 is assigned as it handles the lack of parameters correctly without introducing confusion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Returns trending 2026 color palette combinations with specific hex codes and usage examples.' It specifies the verb ('Returns'), resource ('trending 2026 color palette combinations'), and output details. However, it doesn't explicitly differentiate from sibling tools like 'get_color_guidance' or 'get_modern_trends', which might offer overlapping or related functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like 'get_color_guidance' or 'get_modern_trends', nor does it specify contexts, prerequisites, or exclusions for its use. This leaves the agent without clear direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states what is returned but lacks behavioral details such as whether this is a read-only operation, if it requires authentication, rate limits, or error handling. For a tool with zero annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the key information without any wasted words. It directly states what the tool returns, making it highly concise and well-structured for its purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 specifies the content returned but doesn't cover behavioral aspects or usage context, leaving gaps that could hinder an agent's effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here, but since there are no parameters to explain, it meets the baseline for tools with zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 content it returns ('breakpoints, mobile-first principles, and touch target rules'), which distinguishes it from siblings like 'get_accessibility_guidance' or 'get_typography_guidance'. However, it doesn't specify the verb 'returns' as a distinct action beyond what the name implies, keeping it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 alternatives. With many sibling tools (e.g., 'get_layout_patterns', 'get_design_principles'), the description lacks context on specific scenarios or exclusions, leaving the agent to infer usage based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters4/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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.
Behavior2/5
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 mentions returning patterns and usage guidance, but does not describe key behavioral traits such as the format of the return data, whether it's static or dynamic, potential rate limits, or any authentication needs. This leaves significant gaps for an AI agent to understand how to handle the tool's output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Returns standard layout patterns') and includes additional value ('and when to use them'). There is no wasted text, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity is low (0 parameters, no output schema), the description is somewhat complete but lacks details on behavioral aspects. It covers the purpose and usage context, but without annotations or output schema, it should provide more on what the return looks like (e.g., list of patterns with descriptions) to fully guide the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 no parameter documentation is needed. The description does not add parameter information, which is appropriate, but it could have mentioned the lack of inputs. Baseline is 4 for zero parameters, as the schema fully covers the absence of inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 the verb 'Returns' and specifies the resource 'standard layout patterns' along with examples (F-pattern, Z-pattern, Bento Grid). It distinguishes from siblings like 'get_animation_guidance' or 'get_color_guidance' by focusing on layout patterns, but does not explicitly differentiate from all siblings (e.g., 'get_section_guidance' might overlap).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes 'when to use them,' which provides clear context for usage, implying guidance on application scenarios. However, it does not explicitly state when not to use this tool or name alternatives among siblings, such as 'get_component_guidance' for more specific design elements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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