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Server Quality Checklist

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  • Latest release: v0.9.1

  • Disambiguation5/5

    Each tool has a clearly distinct purpose with no overlap: 'categories' lists capabilities and services, 'compare' analyzes service options with recommendations, and 'execute' routes and runs API calls. The separation between listing, comparing, and executing is unambiguous.

    Naming Consistency5/5

    All tool names follow a consistent verb-only pattern in lowercase, with no mixing of conventions. The naming is straightforward and predictable across the set.

    Tool Count5/5

    Three tools is well-scoped for the server's purpose of managing and executing API services through Hebline. Each tool earns its place by covering a distinct phase: discovery, comparison, and execution.

    Completeness5/5

    The tool set provides complete coverage for the domain: it allows agents to discover capabilities, compare service options, and execute calls with metadata. There are no obvious gaps in the workflow from start to finish.

  • Average 3.2/5 across 3 of 3 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 is failing
  • 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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    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 full burden. It mentions that the tool returns 'result with metadata (service used, cost, latency)', which adds some behavioral context. However, it lacks details on permissions, rate limits, error handling, or side effects, which are important for a tool that executes API calls and routes services.

    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 very concise and front-loaded: it states the core purpose in the first clause and adds return details in parentheses. Every sentence earns its place with no wasted words, making it efficient and well-structured.

    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?

    Given the tool's complexity (executes API calls with routing) and lack of annotations/output schema, the description is moderately complete. It covers the purpose and return metadata, but gaps remain in behavioral details and usage guidelines. It's adequate but has clear room for improvement in context.

    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 parameters. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain parameter interactions or usage examples). Baseline is 3 when schema coverage is high and description doesn't compensate.

    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 clearly states the tool's purpose: 'Route to the best service and execute the API call.' It specifies the action (route and execute) and resource (API call), but doesn't distinguish it from sibling tools like 'categories' or 'compare' which have different purposes. The description is specific but lacks sibling differentiation.

    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?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or other contexts, and offers no explicit when/when-not scenarios. Usage is implied (e.g., for API calls with routing), but no clear alternatives or exclusions are stated.

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

  • 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 implies a read-only operation ('List'), but doesn't specify whether it requires authentication, has rate limits, returns structured data, or involves pagination. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

    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, efficient sentence that directly states the tool's function without fluff. It's front-loaded with the core action ('List') and resource, making it easy to parse. Every word contributes to understanding, achieving ideal conciseness.

    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?

    Given the tool's simplicity (0 parameters, no output schema), the description is adequate but not fully complete. It explains what the tool does but lacks details on return format, error handling, or behavioral constraints. With no annotations to fill gaps, it meets minimum viability but leaves room for improvement in guiding agent usage.

    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 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to compensate for missing param info. A baseline of 4 is appropriate as it avoids redundancy and focuses on the tool's purpose without unnecessary parameter details.

    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 clearly states the tool's purpose: 'List all capabilities Hebline supports and which services are available for each.' It uses specific verbs ('List') and identifies the resource ('capabilities Hebline supports'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools (compare, execute), which prevents a perfect score.

    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?

    The description provides no guidance on when to use this tool versus alternatives like 'compare' or 'execute'. It doesn't mention prerequisites, timing, or contextual triggers. While the purpose is clear, the lack of comparative or conditional guidance limits its utility for an agent deciding between tools.

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

  • 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. It mentions outputs (scores, costs, recommendation) but lacks details on behavioral traits such as data freshness, rate limits, authentication needs, or error handling. This is inadequate for a tool with no annotation coverage.

    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, efficient sentence that front-loads the purpose. It could be slightly more structured by separating key points, but it avoids redundancy and wastes no words.

    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?

    Given the tool's complexity (comparison with multiple outputs), lack of annotations, and no output schema, the description is incomplete. It hints at outputs but doesn't detail format or behavior, leaving gaps for the agent to handle mutations or errors.

    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 fully documents all three parameters. The description adds no additional meaning beyond what the schema provides, such as examples or constraints not in the schema, meeting the baseline for high coverage.

    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 verb 'compare' and the resource 'all available services for a capability', with specific outputs mentioned ('scores, costs, and Hebline's recommendation'). It distinguishes from sibling tools 'categories' and 'execute' by focusing on comparison rather than listing or execution.

    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 versus alternatives like 'categories' or 'execute'. The description implies usage for comparing services but doesn't specify scenarios, prerequisites, or exclusions, leaving the agent to infer context.

    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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