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qinouz

qsw-mcp

by qinouz
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Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation3/5

    read_url and read_url_browser both fetch web content, creating potential confusion; the browser variant's features like login and SPA support help distinguish them, but the overlap remains. read_clipboard_image is clearly distinct.

    Naming Consistency5/5

    All tools follow a consistent 'read_' prefix with a clear object suffix (url, url_browser, clipboard_image), forming a predictable verb_noun pattern throughout the set.

    Tool Count4/5

    With only 3 tools, the set is minimal but appropriately scoped for a content-reading utility covering two modes of web reading and OCR. It is slightly thin but not unreasonably so.

    Completeness4/5

    The domain of reading content is reasonably covered: simple URLs, browser-dependent URLs, and clipboard image OCR. Minor gaps like text clipboard reading or local file support exist, but core use cases are addressed.

  • Average 3.5/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 3 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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 provided, the description carries the burden. It discloses the return types (title, plain text, Markdown) and the absence of login state, but does not mention JS rendering, redirects, or error handling, leaving important behavioral gaps.

    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, front-loaded sentence with no fluff. It efficiently communicates both the action and the expected output in minimal space.

    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 (one parameter, no output schema, no annotations), the description covers the essentials but lacks details on response structure, error cases, or authentication limitations. It is minimally adequate but could be more informative.

    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 for the single 'url' parameter is 100%, so the schema already documents it fully. The description adds no additional parameter-specific details, making a baseline score of 3 appropriate.

    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 reads web content and returns title, plain text, and Markdown format, with a note about no login state. It does not explicitly differentiate from the sibling read_url_browser, but the core purpose is specific and unambiguous.

    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 explicit guidance on when to use this tool versus alternatives. The '无登录状态' note implies a limitation but does not state preferred use cases or when to choose read_url_browser instead.

    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?

    With no annotations, the description carries the full burden, but it only states the basic read/OCR function. It does not disclose what happens if the clipboard lacks an image, whether clipboard content is modified, or what the return format is.

    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, information-dense sentence with no filler or redundant content, making it concise 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?

    The tool is simple with two optional parameters, but the absence of an output schema and annotations means the description should mention return format or prerequisites (e.g., clipboard must contain an image). The current description is partially complete but lacks these contextual details.

    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?

    The input schema already documents both parameters completely (100% coverage), so the description adds no additional parameter context. A baseline of 3 is appropriate given the schema does the heavy lifting.

    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 (read from system clipboard and OCR) and the resource (clipboard image), and it distinguishes itself from sibling URL-reading tools by focusing on clipboard source.

    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 context is implied (use when an image is in the clipboard and you need OCR), but there is no explicit guidance on when to use this tool versus alternatives, nor any mention of exclusions such as whether it works with non-image clipboard content.

    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 carries the burden. It discloses browser-based execution and support for authentication/dynamic content, which suggests JavaScript rendering. However, it omits behavioral traits like potential slowness, failure modes, or whether it can be headless. Some transparency is given, 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, dense sentence that immediately conveys the core functionality and distinguishing features. It contains no filler and is perfectly front-loaded, making it highly efficient.

    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?

    With no output schema or annotations, the description must compensate but does not explain what the tool returns (e.g., text, HTML, screenshot) or any limitations of browser-based reading. Given the complexity of the tool, this is a significant gap, making the description incomplete.

    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?

    The input schema provides 100% description coverage for all parameters, including url, waitFor, and useExisting. The tool description adds no additional parameter-level meaning beyond the schema, so the baseline of 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 clearly states a specific verb+resource: '使用浏览器读取网页' (use browser to read web pages), and the parenthetical features (login state, cookies, SPA pages) distinguish it from sibling tools like read_url which likely performs simple HTTP fetches. This provides a clear differentiation.

    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 for scenarios requiring login, cookies, or SPA rendering through the parenthetical remark, but it does not explicitly state when to prefer this over read_url or provide exclusions. Guidance is implied rather than explicit.

    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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