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goofypluto999

cv-mirror-mcp

by goofypluto999
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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation4/5

    The tools have distinct purposes: analyze_cv for all vendors, lint_for_vendor for a single vendor, and get_express_url for a visual URL. However, analyze_cv and lint_for_vendor both analyze CVs, which could cause minor confusion if descriptions are not read carefully.

    Naming Consistency3/5

    Tool names follow a verb_noun pattern but with inconsistency: 'analyze_cv' and 'get_express_url' are direct, while 'lint_for_vendor' uses a preposition. The verb 'lint' is less standard than 'analyze'.

    Tool Count4/5

    With 3 tools, the set is small but well-scoped for the domain of CV ATS analysis. It covers the essential operations without being overly sparse.

    Completeness4/5

    The tool set covers comprehensive analysis, vendor-specific linting, and a visual companion tool. Minor gaps like listing vendors or handling multiple files are absent but not critical for the core functionality.

  • Average 4/5 across 3 of 3 tools scored.

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

    • 0 of 1 community issues answered or closed 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 MIT License.

  • 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 full burden. It does not explain whether the tool is read-only, what side effects exist, or what the output format is. The term 'lint' implies analysis but lacks detail.

    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 sentences, front-loaded with the core action and constraint. Each sentence adds value: one states the purpose and allowed vendors, the other gives usage examples. No wasted words.

    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?

    Despite its simplicity, the tool has no output schema and the description does not explain what the lint result looks like (e.g., a score, a list of issues). The user cannot infer the return format without additional 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?

    Input schema has 100% coverage with clear descriptions. The description adds context for the vendor enum by specifying use cases, but adds no extra meaning for the path parameter beyond its schema description.

    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 states 'Run lint for ONE specific ATS vendor only', with a clear verb and resource. It lists the allowed vendors and uses examples to distinguish from siblings like analyze_cv, making the purpose unambiguous.

    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 provides when-to-use examples ('when the user asks something vendor-specific like...'). Does not explicitly state when not to use or name an alternative tool, though the sibling names imply a general CV analysis 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, so description carries full burden. It discloses tool reads PDF/DOCX, runs against 5 parsers, and returns findings. Does not mention file size limits, processing duration, or if file is uploaded elsewhere, but is largely transparent about its operation.

    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 focused sentences: first defines action and output, second provides usage examples. No unnecessary words. Excellent front-loading of purpose.

    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?

    Despite no output schema, description explains return types (per-vendor lint findings, risk score, fixes). Mentions supported file types. Could add error handling details (e.g., missing file), but otherwise complete for a single-parameter tool.

    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?

    Input schema has 100% coverage with description for the single 'path' parameter. The description does not add further details beyond schema, but schema itself is sufficient. Baseline 3 applies.

    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 explicitly states the tool analyzes CVs against 5 ATS parsers, returning per-vendor lint findings, risk score, and fixes. It clearly distinguishes from siblings by covering multiple vendors (vs. lint_for_vendor which likely targets one).

    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?

    Description provides explicit user query triggers ('is my CV ATS-friendly', 'will my resume pass [vendor]', 'why am I not getting interviews') and mentions file path requirement. Lacks explicit when-not-to-use or mention of sibling alternatives, but context is clear.

    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 provided, so description carries full burden. States it returns a URL, implying read-only, but does not explicitly declare non-destructive behavior or other constraints.

    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 sentences, no unnecessary words, front-loaded with purpose. Highly efficient.

    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?

    Adequate for a zero-parameter, no-output-schema tool. Explains function and usage context. Minor gap: doesn't explicitly state no input needed, but schema implies it.

    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?

    No parameters (schema coverage 100%), baseline 4. Description adds meaning by explaining the purpose of the URL beyond the empty schema.

    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?

    Clear verb+resource: 'Returns the URL' for a specific visual tool (CV Mirror). Distinguishes from siblings (analyze_cv, lint_for_vendor) by offering a different capability.

    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?

    States when it's useful (visual reading-order overlay, avoiding file path sharing). Does not explicitly exclude alternative uses but context is clear.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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