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Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'get_allure_report' has a single, clearly defined purpose of reading Allure reports and returning JSON data.

    Naming Consistency5/5

    The single tool name 'get_allure_report' follows a clear verb_noun pattern (get + report). Since there is only one tool, consistency is inherently perfect with no deviations to assess.

    Tool Count2/5

    The server has only one tool, which feels thin for a reporting domain like Allure. A single tool for reading reports lacks essential operations such as generating, listing, or managing reports, making it under-scoped for typical use cases.

    Completeness2/5

    The tool surface is severely incomplete for an Allure reporting server. It only provides a 'get' operation for reports, missing critical functions like creating reports, listing available reports, updating report data, or deleting reports, which are essential for full lifecycle coverage.

  • Average 2.4/5 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 Apache 2.0.

  • 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 behavioral disclosure. It mentions reading and returning JSON data, but fails to disclose critical traits: whether this is a read-only operation (implied by 'read' but not explicit), potential side effects (e.g., file access permissions), error handling, or performance aspects (e.g., large report processing). The description adds minimal value beyond the basic action.

    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 very concise—a single sentence with no wasted words—and front-loaded with the core action. However, it is under-specified rather than efficiently concise; it could benefit from slightly more detail without losing brevity. It earns a high score for structure but loses a point due to under-specification.

    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?

    Given the complexity (a tool to read and parse reports), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It does not explain the return format beyond 'json data' (e.g., structure, keys), error conditions, or dependencies. For a tool with one parameter and no structured support, more context is needed to be adequately helpful.

    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 0%, with 1 parameter ('results_dir') undocumented in the schema. The description does not compensate by explaining what 'results_dir' means (e.g., path to Allure results directory, expected format), its role in reading the report, or any constraints. This leaves the parameter's semantics unclear, failing to add meaning beyond the bare schema.

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

    Purpose3/5

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

    The description states the tool 'read[s] allure report and return[s] json data', which provides a basic verb+resource combination ('read allure report') and outcome ('return json data'). However, it's vague about what constitutes an 'allure report' (e.g., test results, specific file format) and doesn't differentiate from siblings (though none exist). It avoids tautology by not merely restating the name, but lacks specificity.

    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 provided on when to use this tool—there are no alternatives mentioned (sibling tools are none), no context about prerequisites (e.g., requires an existing report directory), and no exclusions or comparisons. The description implies usage for reading reports but offers no further direction.

    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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