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kalimuthu-a

EDS Block Analyser MCP Server

by kalimuthu-a
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JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.1

  • Disambiguation5/5

    With only one tool, there is no ambiguity or overlap. The tool's purpose is clearly defined and distinct from any potential alternatives.

    Naming Consistency5/5

    The single tool name follows a descriptive pattern and has no conflicting conventions. Consistency is trivially maintained with one tool.

    Tool Count3/5

    The server has only one tool, which feels thin for a typical MCP server. While the tool is non-trivial and serves a specific purpose, the limited scope makes the count borderline.

    Completeness5/5

    The tool fully addresses its stated purpose of generating a UI architect prompt for UI block analysis and estimation. There are no obvious gaps or missing operations for this narrow domain.

  • Average 3.4/5 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

  • This repository is licensed under MIT License.

  • 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 disclosing behavior. It only says a prompt is returned; it does not mention whether the operation is read-only, any side effects, or the format/content of the prompt. This is insufficient for a tool with no annotation support.

    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 sentence that is concise and front-loaded. It conveys the core purpose without any fluff or redundant information, 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?

    The tool is simple with no parameters and no output schema. The description states what it produces (a prompt), but the term 'UI block conversion' is ambiguous and not explained. Given the lack of additional structure, the description could be slightly more detailed about the nature of the prompt or expected usage, resulting in a minimally adequate score.

    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 coverage is 100% (empty). According to the rubric, a 0-parameter tool gets a baseline of 4. The description does not add parameter details, but none are needed given the empty schema.

    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 uses a specific verb 'Get' and identifies the resource as a 'UI architect prompt' for analyzing and estimating UI block conversion. It clearly states the tool's function, though 'UI block conversion' is somewhat specialized and could be clearer.

    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?

    No explicit usage guidance is provided, but the purpose is implied: you would use this tool when you need a UI architect prompt for UI block conversion. With no sibling tools or alternatives mentioned, explicit when/when-not guidance is not critical, but it would still be helpful.

    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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