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xiaobenyang-com

Logo-Analyze

by xiaobenyang-com
OverviewSchemaRelated ServersScoreDiscussions
TypeScript

Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation2/5

    The two tools have significant overlap in purpose, as both can return the best logo URL. 'analyze_logo' does this optionally via a parameter, while 'get_best_logo_url' is dedicated to it, creating ambiguity about which to use for that specific task. Their descriptions suggest different primary functions (analysis vs. extraction), but the shared capability blurs the boundaries.

    Naming Consistency4/5

    Both tools use a clear verb_noun pattern ('analyze_logo' and 'get_best_logo_url'), making them readable and predictable. The naming is mostly consistent, with minor deviations in verb choice ('analyze' vs. 'get') that reflect their different focuses but don't break the overall pattern.

    Tool Count2/5

    With only 2 tools, the server feels under-scoped for a logo analysis domain. This limited set may not cover essential operations like logo validation, comparison, or batch processing, making it thin and potentially incomplete for typical agent workflows in this area.

    Completeness2/5

    The tool surface has significant gaps for logo analysis. It lacks basic CRUD operations (e.g., no upload, delete, or update tools) and misses common functionalities like logo format conversion, color analysis, or batch processing. The two tools provide limited coverage, likely causing agent failures in broader tasks.

  • Average 3/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • 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 Apache 2.0.

  • This repository includes a README.md file.

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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 extraction and returning a URL, but doesn't describe how 'best' is determined, potential errors (e.g., if no logo is found), rate limits, or authentication needs. This leaves significant gaps in understanding the tool's behavior.

    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 concise and front-loaded, consisting of a single sentence that states the core purpose. There's no wasted text, though it could be slightly more informative without losing efficiency.

    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 tool's complexity (extracting a 'best' logo from a website), lack of annotations, no output schema, and low parameter coverage, the description is incomplete. It doesn't explain the extraction logic, return format, error handling, or other behavioral aspects needed for effective use.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 1 parameter (url) with 0% description coverage, and the tool description provides no information about the parameter. It doesn't explain what the 'url' input represents (e.g., website URL to analyze), expected format, or constraints, failing to compensate for the low 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 tool's purpose: '从网站提取并返回最佳Logo的URL地址' (extract and return the best logo URL from a website). It specifies the verb (extract/return) and resource (logo URL), though it doesn't explicitly differentiate from the sibling tool 'analyze_logo' beyond stating it's for scenarios where only the best logo URL is needed.

    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 provides some usage context: '适用于只需要获取最佳Logo URL的场景' (suitable for scenarios where only the best logo URL needs to be obtained). This implies when to use it (when you just need the URL) but doesn't explicitly state when not to use it or mention the sibling tool 'analyze_logo' as an alternative for more detailed analysis.

    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 that the tool analyzes logo information and supports an onlyBestUrl parameter to return only the best logo's URL, but it lacks details on what 'best' means, how analysis is performed, potential rate limits, error conditions, or output format. This leaves significant gaps in understanding the tool's behavior.

    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 concise and front-loaded, stating the main purpose in the first part and adding parameter-specific information in the second. Both sentences earn their place by providing essential details without unnecessary elaboration, though it could be slightly more structured for clarity.

    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 of analyzing logos (which may involve image processing), no annotations, no output schema, and low schema description coverage, the description is incomplete. It doesn't explain what 'quality' means, how results are returned, or any limitations, making it insufficient for an agent to fully understand the tool's context and usage.

    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 0%, so the description must compensate. It adds meaning for the 'onlyBestUrl' parameter by explaining it returns only the best logo's URL, but it doesn't clarify the 'url' parameter's purpose or format. With 2 parameters and partial coverage in the description, this meets the baseline for minimal adequacy but doesn't fully compensate for the schema gap.

    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: '分析Logo的基本信息（尺寸、格式、质量等）' (analyze logo's basic information including dimensions, format, quality, etc.). It specifies the verb 'analyze' and resource 'logo' with concrete attributes. However, it doesn't explicitly differentiate from the sibling tool 'get_best_logo_url' beyond mentioning the onlyBestUrl parameter.

    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 through the mention of 'onlyBestUrl参数只返回最佳Logo的URL' (onlyBestUrl parameter returns only the best logo's URL), suggesting this tool can be used for detailed analysis or just to get the best URL. However, it doesn't provide explicit guidance on when to use this tool versus the sibling 'get_best_logo_url' or any other alternatives, leaving the distinction unclear.

    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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