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byebyebruce

infographic-mcp

by byebyebruce
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap. The tool has a clear, singular purpose: rendering infographics from DSL syntax.

    Naming Consistency5/5

    The single tool name 'render_infographic' follows a clear verb_noun pattern and is descriptive. With only one tool, naming consistency is inherently perfect.

    Tool Count3/5

    A single tool feels thin for a dedicated server, though the tool itself is substantial and handles a complex rendering task. It falls at the borderline of acceptable scope.

    Completeness2/5

    The server provides only a render function with no way to discover available templates, validate DSL syntax, or list supported options. Agents must rely on external knowledge, creating a significant gap in the tool surface.

  • Average 4.1/5 across 1 of 1 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

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  • 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

  • Behavior3/5

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

    With no annotations, the description must disclose behavior. It alerts users that the DSL is space-separated key-value (NOT YAML), which is a critical pitfall, and states the output is a PNG. However, it omits error handling, invalid-syntax behavior, and other potential constraints, leaving some transparency gaps.

    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 longer than average but justified by the complexity of the DSL. The code block and template list are necessary for correct usage. Each sentence contributes value, though the content could be slightly trimmed without losing essential information.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The tool uses a complex DSL, so the example and template disclosure are essential. It states the return type (PNG) and provides template examples, but does not cover output dimensions (though schema parameters define this) or error behavior. Overall, it is largely complete for the tool's complexity.

    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?

    All parameters have schema descriptions (100% coverage), giving a baseline of 3. The description significantly enriches the 'syntax' parameter by providing a complete DSL example and template list, adding meaning beyond the schema's one-line description. Other parameters remain adequately covered by the schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states 'Render an infographic from DSL syntax and return as PNG image', specifying both the operation (render) and the resource (infographic from DSL syntax), along with the output format. This is a precise, verb+resource statement that fully distinguishes the tool's purpose.

    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 provides a detailed DSL syntax example and a template list, giving clear context on how to construct input. It doesn't mention alternatives since none are listed as siblings, but it does not explicitly state when to use the tool instead of others. The context is clear and actionable.

    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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  • Evaluate tool definition quality.

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