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vinsenzo83

command-map-mcp

by vinsenzo83
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: cmdmap_list browses available tasks, and cmdmap_build generates a prompt for a specific task ID. No overlap or confusion possible.

    Naming Consistency5/5

    Both tools follow a consistent 'cmdmap_verb' pattern (cmdmap_list, cmdmap_build), using snake_case and clear verb-noun structure.

    Tool Count4/5

    With only 2 tools, the set is on the low end but appropriate for the focused purpose of browsing and building command maps. It covers the core workflow without unnecessary overhead.

    Completeness5/5

    The tool surface fully covers the server's purpose: list available tasks and retrieve a built prompt. No missing operations like editing or customizing are expected for this domain.

  • Average 4.4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 2 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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

  • Behavior4/5

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

    No annotations provided, so description carries full burden. It implies read-only behavior ('조회' - inquiry) and describes only list retrieval. No contradictions, but could explicitly state idempotence or readonly.

    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?

    Two concise sentences, front-loaded with key details (6 domains, 121 tasks, filtering, intended use). No wasted words.

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

    Completeness5/5

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

    For a simple tool with one optional parameter and sibling context, the description provides everything needed: purpose, filtering, and workflow link to cmdmap_build.

    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?

    Schema coverage is 100% with a description on the parameter. The description's mention of domain filtering adds no new meaning beyond the schema. Baseline 3 is appropriate.

    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 it returns a list of 121 tasks across 6 domains, with optional filtering by domain. It distinguishes itself from sibling cmdmap_build by specifying the workflow: browse tasks here, then use cmdmap_build with the selected id.

    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?

    Explicitly states when to use this tool: to browse tasks and pick an id for cmdmap_build. No exclusion criteria are given, but the context is clear for this simple list tool.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

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

    No annotations are provided, so the description carries full burden. It discloses the automatic insertion of a question prompt when 'context' is empty and outlines the 6-part template. It could be more explicit about non-destructive nature, but overall transparent.

    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 two sentences, front-loaded with the main purpose, and the second sentence adds a specific and important behavioral note. Every sentence earns its place without redundancy.

    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?

    Given the complexity (3 parameters, no output schema, no annotations), the description adequately explains the function and key behaviors. It mentions the 6-part template output but could provide more detail on the return value format. Still largely complete.

    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?

    Schema coverage is 100% with clear descriptions for all parameters. The overall description adds value by explaining the behavioral effect of leaving 'context' empty (auto-insertion of 'ask 3 questions' instruction), which is not in schema 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 takes a task ID and returns a complete prompt using a specific 6-part template. It uses a specific verb ('returns') and resource ('prompt text'), and it distinguishes itself from the sibling tool 'cmdmap_list' which lists tasks.

    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 clear context about usage, including the special behavior when 'context' is left empty. It implicitly guides the agent to use this after selecting a task with cmdmap_list, though it does not explicitly state when not to use it or name alternatives.

    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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Glama performs regular codebase and documentation scans to:

  • 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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