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xiaobenyang-com

xiaobenyang-mcp-2-2

by xiaobenyang-com
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TypeScript

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves a list of dish names, while the other fetches detailed content for a specific dish. There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool based on the task.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (get_all_dishes and get_dish_content), using 'get' as the verb and descriptive nouns. The naming is predictable and readable, with no deviations or mixed conventions.

    Tool Count2/5

    With only two tools, the server feels thin and under-scoped for a dish-related domain. While it covers basic retrieval, it lacks essential operations like creating, updating, or deleting dishes, which limits its utility and coherence as a complete toolset.

    Completeness2/5

    The toolset is severely incomplete for a dish management domain. It only provides read operations (list and get details), missing critical CRUD functions such as create_dish, update_dish, and delete_dish. This creates significant gaps that will likely cause agent failures when trying to perform full lifecycle management.

  • Average 3/5 across 2 of 2 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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. The description only states the basic operation without mentioning important behavioral aspects like whether this is a read-only operation, what happens if the dish doesn't exist, what format the detailed content returns in, or any rate limits or authentication requirements. For a lookup tool with zero annotation coverage, this is inadequate.

    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 extremely concise - a single sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration. It's appropriately sized for a simple lookup tool and gets straight to the point.

    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?

    For a tool with no annotations, no output schema, and minimal parameter documentation, the description is insufficiently complete. While the tool appears simple (single parameter lookup), the description doesn't address what '详细内容' (detailed content) includes, how errors are handled, or what format the response takes. The agent would need to guess about the tool's behavior and output.

    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?

    With 0% schema description coverage and 1 parameter, the description adds minimal value beyond what the schema provides. The description mentions '菜品名称' (dish name) which corresponds to the 'dishName' parameter, but provides no additional context about format expectations, character limits, or examples. The schema already indicates it's a required string parameter, so the description doesn't significantly enhance understanding.

    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: '根据提供的菜品名称获取其详细内容' (Get detailed content based on provided dish name). It specifies the verb '获取' (get) and resource '菜品详细内容' (dish detailed content). However, it doesn't explicitly differentiate from its sibling 'get_all_dishes', which appears to be a list operation versus this lookup operation.

    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. There's no mention of when to use 'get_dish_content' versus 'get_all_dishes', nor any context about prerequisites, error conditions, or appropriate use cases. The description only states what the tool does, not when to use it.

    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 states the tool retrieves a list of dish names, implying a read-only operation, but doesn't specify aspects like whether it requires authentication, rate limits, error handling, or if the list is paginated. The description is minimal and lacks behavioral context 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, efficient sentence in Chinese that directly states the tool's function without any unnecessary words. It's front-loaded with the core purpose and appropriately sized for a simple tool with no parameters.

    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 annotations, no output schema), the description is minimally adequate. It explains what the tool does but lacks details on behavioral traits, output format beyond 'list of names,' or usage context. For a read-only tool with no parameters, it meets the basic requirement but could be more informative about the return value or operational constraints.

    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 input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details, but since there are no parameters, this is acceptable. The baseline for 0 parameters is 4, as the description doesn't need to compensate for missing schema information.

    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: '获取所有可用菜品的名称列表 (菜单)' translates to 'Get a list of names of all available dishes (menu).' It specifies the verb ('get'), resource ('all available dishes'), and output format ('list of names'). However, it doesn't explicitly differentiate from its sibling 'get_dish_content' beyond implying this tool returns names only versus potentially detailed content.

    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 the sibling tool 'get_dish_content' or clarify scenarios where one might be preferred over the other, such as needing dish names only versus full details. Usage is implied but not explicitly stated.

    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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