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lahuman

mcp-variable

by lahuman
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TypeScript
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Server Quality Checklist

50%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    With only one tool, there is no ambiguity or overlap with other tools. The tool's purpose is clear and distinct.

    Naming Consistency5/5

    The single tool name 'convert_terms' follows a clear verb_noun pattern, which is consistent and predictable.

    Tool Count5/5

    The server has exactly one tool, which is appropriate for its focused purpose of converting Korean business terms. No redundancy exists.

    Completeness4/5

    The tool covers both directions of conversion (Korean to physical names and back), fulfilling its core purpose. Minor gaps include lack of dictionary management features, but the tool is complete for conversion tasks.

  • Average 2.9/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 24 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

  • Behavior2/5

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

    With no annotations, the description must disclose all behavioral traits. It mentions using a CSV dictionary but fails to explain behavior for missing terms, multiple candidates, or whether the operation is read-only. The maxCandidates parameter hints at multiple results, but this is not stated.

    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 sentence that efficiently conveys the main function. It is front-loaded and to the point, though it could include more detail without being overly verbose.

    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 tool with 4 parameters, enums, and an output schema, the description is minimal. It does not explain the output format or provide enough context for correct usage, leaving gaps that the agent must infer.

    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?

    Schema description coverage is only 25%, and the main description does not explain any parameters. It indirectly references the conversion direction but does not clarify the meaning of direction, outputCase, or maxCandidates. The tool would benefit from parameter-level descriptions.

    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 the tool's purpose: converting Korean business terms to physical names and vice versa. It specifies the use of a CSV dictionary and the two directions, making it easy for an agent to understand the core function.

    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 given on when to use this tool versus alternatives or when not to use it. The description implies conversion but lacks context about prerequisites or scenarios.

    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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