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Server Quality Checklist

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  • Latest release: v1.1.2

  • Disambiguation5/5

    Each tool has a completely distinct purpose: fetching documentation, analyzing build errors, and checking Swift evolution proposals. There is no overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent snake_case pattern with descriptive names combining verbs and nouns (e.g., fetch_latest_apple_docs). No mixing of conventions or vague terms.

    Tool Count4/5

    Three tools is a small but well-scoped set for an Apple development helper. Each tool covers a core area without being overly narrow, though adding a few more (e.g., simctl, provisioning) could be justified.

    Completeness4/5

    The tools address documentation, error diagnosis, and language evolution—key areas for Apple developers. Missing tools like provisioning profiles or Xcode version management are minor gaps, and the current set avoids dead ends.

  • Average 4/5 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 passing
  • 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.

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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 full burden. It discloses that it provides classification, suggestions, and documentation links, and supports specific error types. However, it does not mention potential side effects (e.g., network calls), privacy implications, or limitations (e.g., offline 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 concise, using a bullet list for capabilities and a final line for supported errors. It is front-loaded with the main action and has no redundant information.

    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?

    The description covers the tool's purpose, capabilities, and supported error types. However, it lacks details about the output format or behavior when no errors are found. Given no output schema, a brief mention of return value would enhance completeness.

    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%, so baseline is 3. The description adds no significant parameter details beyond the schema; it merely reiterates supported error types. The descriptions in the schema are already clear.

    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 analyzes Xcode build logs and error messages, listing specific capabilities (classification, fix-it suggestions, documentation links). It distinguishes itself from siblings (fetch_latest_apple_docs, swift_evolution_check) by focusing on diagnostic analysis.

    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 usage when encountering Xcode build errors, but does not provide explicit when-to-use or when-not-to-use guidance, nor alternatives. The context from siblings helps, but no direct exclusions.

    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?

    No annotations are provided, so the description must disclose behavior. It states what is returned (documentation summary, code examples, availability) but does not mention side effects, authorization needs, or any limitations. The tool is likely read-only but that is not explicit.

    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 concise with a single sentence followed by clear examples. Every part serves a purpose 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?

    The description covers the tool's purpose, expected input examples, and return content. Given the tool's low complexity (3 params, no output schema) and lack of annotations, this is sufficient for an agent to use it effectively.

    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 description coverage is 100%, so the schema already documents all three parameters. The description adds value by providing example values and clarifying usage contexts, which helps the agent understand how to use parameters effectively.

    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 ('fetches the latest Apple Developer Documentation') and the resource ('specific API, framework, or symbol'). Examples illustrate the scope. The tool is distinct from siblings like xcode_diagnostic_analyzer and swift_evolution_check.

    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?

    Usage is implied through examples but no explicit guidance on when to use this tool vs alternatives or when not to use it. No exclusions or prerequisites are mentioned.

    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?

    No annotations are provided, so the description bears full responsibility. It describes what information is returned (proposal status, compiler flags, migration guidance) but does not disclose whether the operation is read-only, requires authentication, or has any side effects. This is adequate but not thorough for a check tool.

    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 concise with a clear first sentence stating purpose, followed by bullet points. It is well-structured and front-loaded, though it could be slightly tighter by removing the 'Use this to verify:' preamble.

    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 2 parameters, no output schema, and no annotations, the description provides sufficient information to understand tool behavior and results. It covers what the tool checks and what it returns (proposal number, status, etc.), but lacks error handling 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?

    Schema description coverage is 100%, so baseline is 3. The description adds value beyond schema by providing concrete examples of features ('nonisolated(unsafe)', 'typed throws') and listing uses like 'Required compiler flags or availability annotations', which help clarify parameter usage.

    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 'Checks' and resource 'status of Swift language features against Swift Evolution proposals'. It lists specific verifications (availability, proposal status, compiler flags, migration guidance) and distinguishes from siblings (fetch_latest_apple_docs, xcode_diagnostic_analyzer) by focusing on Swift Evolution proposals.

    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 'Use this to verify:' followed by four bullet points describing when to use the tool. It provides clear context but does not include when not to use or direct comparisons to sibling tools, though the purpose differentiation is implied.

    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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