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Server Quality Checklist

67%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose with no ambiguity: two tools retrieve specific media by ID (image vs. video), and two tools search for media (images vs. videos). The resource type (image/video) and action (get/search) are consistently differentiated, making misselection unlikely.

    Naming Consistency5/5

    Tool names follow a perfect verb_noun pattern throughout: all use snake_case with consistent verbs ('get' for retrieval, 'search' for searching) and clear nouns ('image_by_id', 'video_by_id', 'images', 'videos'). There are no deviations or mixed conventions.

    Tool Count5/5

    With 4 tools, this server is well-scoped for its Pixabay media retrieval purpose. Each tool earns its place by covering essential operations: retrieval and search for both images and videos, which is appropriate and not overly complex or thin.

    Completeness5/5

    The tool surface is complete for the domain of accessing Pixabay media. It provides full coverage for both images and videos with retrieval (get) and discovery (search) operations, leaving no obvious gaps or dead ends for an agent working with this API.

  • Average 3.1/5 across 4 of 4 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • No commit activity data available
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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      ]
    }

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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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'royalty-free' which hints at licensing, but fails to describe critical behaviors like pagination (implied by 'page' and 'per_page' parameters but not explained), rate limits, authentication requirements, or what the search results actually return. For a search tool with 13 parameters, this leaves significant 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 states the core purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

    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?

    For a search tool with 13 parameters and no output schema, the description is inadequate. It doesn't explain what the search returns (e.g., image metadata, URLs, licensing details), how results are structured, or any behavioral constraints. With no annotations and no output schema, the description should provide more context about the tool's operation and results.

    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, providing detailed documentation for all 13 parameters including defaults, constraints, and enums. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline of 3 where 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 action ('Search for') and resource ('royalty-free images on Pixabay'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'search_videos', which searches for videos on the same platform, leaving some ambiguity about when to choose one over the other.

    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 like 'search_videos' or 'get_image_by_id'. There's no mention of prerequisites, typical use cases, or any context that would help an agent decide between this and sibling 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'royalty-free videos on Pixabay,' which hints at licensing and source, but lacks critical details like rate limits, authentication needs, pagination behavior, error handling, or what the response format includes (e.g., video metadata). For a search tool with 11 parameters, this is insufficient.

    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 without unnecessary words. It's appropriately sized for a search tool, with every part earning its place by specifying the action, resource, and platform concisely.

    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 complexity (11 parameters, no annotations, no output schema), the description is incomplete. It lacks information on behavioral traits (e.g., rate limits, response format), usage guidelines, and output expectations. For a search tool with many filtering options, more context is needed to guide effective use.

    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 description adds no parameter-specific information beyond what's in the input schema, which has 100% coverage with detailed descriptions for all 11 parameters. The baseline is 3 because the schema adequately documents parameters, and the description doesn't compensate with additional context like default behaviors or usage examples.

    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: 'Search for royalty-free videos on Pixabay.' It specifies the action (search), resource (videos), and platform (Pixabay), distinguishing it from sibling tools like search_images. However, it doesn't explicitly differentiate from get_video_by_id beyond the search vs. get 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?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like search_images or get_video_by_id, nor does it specify any prerequisites, exclusions, or contextual cues for selection. Usage is implied by the name 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?

    With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool retrieves a video, implying a read-only operation, but doesn't mention any behavioral traits like authentication needs, rate limits, error handling, or what happens if the ID is invalid. This leaves significant gaps 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.

    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 wasted words. It's appropriately sized and front-loaded, making it easy to understand quickly.

    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 doesn't explain what the tool returns (e.g., video metadata, URL, or full details), error conditions, or other contextual details needed for effective use. For a tool with no structured support, this description leaves too many gaps.

    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 schema description coverage is 100%, with the single parameter 'id' fully documented in the schema as 'Pixabay video ID'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints, so it meets the baseline for high schema coverage.

    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 verb ('retrieve') and resource ('specific video by its Pixabay ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_image_by_id' or 'search_videos', which would require mentioning it's for videos only (not images) and for direct ID lookup (not search).

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies usage when you have a specific video ID, but doesn't provide explicit guidance on when to use this vs. alternatives like 'search_videos' for broader queries or 'get_image_by_id' for images. It lacks clear when-not-to-use statements or named alternatives, leaving some ambiguity.

    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. It states the tool retrieves an image, implying a read-only operation, but doesn't mention any behavioral traits like authentication requirements, rate limits, error handling, or what happens if the ID is invalid. This leaves significant gaps for an agent to understand how to use it safely and effectively.

    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 fluff or redundancy. It's appropriately sized for a simple retrieval tool and front-loaded with the essential information, making it easy for an agent 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 low complexity (single parameter, no annotations, no output schema), the description is minimally adequate. It covers the basic purpose but lacks details on behavior, error cases, or output format, which could hinder an agent's ability to use it correctly in all scenarios. Without annotations or output schema, more context would be beneficial.

    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 schema description coverage is 100%, with the single parameter 'id' clearly documented as 'Pixabay image ID'. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't need to.

    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 action ('Retrieve') and resource ('a specific image by its Pixabay ID'), making the purpose immediately understandable. It distinguishes from sibling tools like 'search_images' by focusing on retrieval of a single known item rather than searching. However, it doesn't explicitly contrast with 'get_video_by_id' beyond the resource type.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implies usage when you have a specific Pixabay ID for an image, suggesting it's for known-item retrieval rather than discovery. However, it doesn't explicitly state when NOT to use it (e.g., vs. 'search_images' for unknown IDs) or name alternatives, leaving some ambiguity about tool selection in edge cases.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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