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Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools are clearly distinct: one performs a commit action and the other retrieves status information. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern: commit_to_gitown and get_town_status. The naming is predictable and clear.

    Tool Count3/5

    With only 2 tools, the set is thin, but it aligns with the narrow scope of the server (commit and view status). It feels minimal yet not excessive for the apparent purpose.

    Completeness4/5

    The server covers the two core operations needed for its gamified commit system: creating a commit and viewing the resulting status/ranking. Minor gaps exist (e.g., detailed commit history or per-agent building views), but the primary lifecycle is covered.

  • Average 3.9/5 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
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  • This repository includes a README.md file.

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

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      "maintainers": [
        "your-github-username"
      ]
    }

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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 carries the burden of disclosing behavioral traits. It discloses the required GitHub token permission and the building-growth effect, but does not explain failure modes, return values, or whether the commit is immediately pushed.

    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?

    Three concise sentences, front-loaded with the primary purpose, followed by the effect and the auth prerequisite. 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.

    Completeness3/5

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

    The description covers the essential purpose, effect, and auth requirement, but lacks details on response behavior, error handling, or how the outcome will be observed. Given no output schema, this leaves a meaningful gap for a complete invocation.

    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 description coverage is 100%, so the schema already documents all three parameters. The description adds limited value beyond the schema, only reiterating the token requirement rather than enriching parameter meaning.

    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 action ('Crea un commit') and the target resource ('repositorio de Gitown'), with a specific scope (on behalf of the agent). It also differentiates from the sibling tool get_town_status by emphasizing the write/commit operation vs status checking.

    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 an implicit usage context (commit actions to grow the building) and states the token prerequisite. However, it does not explicitly contrast with get_town_status or offer when-not-to-use guidance, leaving the user to infer the appropriate context.

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

  • Behavior3/5

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

    With no annotations, the description carries the full burden. It states the tool 'returns' the current state, which implies read-only behavior, but does not explicitly confirm no side effects, permission requirements, or return format details. Adequate for a simple getter but not comprehensive.

    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, direct sentence that front-loads the main action and lists the output contents. No filler or redundant phrasing.

    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?

    For a simple zero-parameter tool with no output schema, the description covers the key return values (commits, ranking, tiers). It is complete enough to set expectations, though it could elaborate on the ranking format or tier details.

    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 input schema has zero parameters, so the baseline is 4. The description does not need to explain parameters as none exist, and the schema coverage is trivially complete.

    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 returns the current Gitown status, listing three specific pieces of data: number of commits, contributor ranking, and building tiers. The verb 'Devuelve' and resource 'Gitown' are specific, and the sibling 'commit_to_gitown' is distinctly different.

    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 this is a read/status tool and that commit_to_gitown is the write/action tool, but it never explicitly states when to choose this tool over alternatives. No usage context or exclusions are provided, only the basic function.

    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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