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xiaobenyang-com

cook-tool

Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: get_all_dishes retrieves a list of dish names (menu), while get_dish_content fetches detailed content for a specific dish based on its name. There is no overlap or ambiguity between these operations.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'get_' prefix and snake_case naming (get_all_dishes, get_dish_content). The naming is predictable and readable throughout.

    Tool Count2/5

    With only 2 tools, the server feels thin for a cooking/recipe domain. It lacks essential operations like creating, updating, or deleting dishes, which limits its utility and scope. A minimal CRUD set would typically have at least 3-4 tools.

    Completeness2/5

    The tool surface is severely incomplete for a cooking domain. It only provides read operations (get all and get details), missing create, update, delete, search, or other lifecycle management tools. This will likely cause agent failures when trying to perform full workflows.

  • 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.

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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 for behavioral disclosure. The description only states what the tool does (get details), but doesn't disclose any behavioral traits like error handling, response format, whether it's idempotent, performance characteristics, or authentication requirements. For a tool with no annotation coverage, this is a significant gap.

    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 zero waste or unnecessary verbiage. While it may be too brief for completeness, as a standalone statement it's perfectly structured and front-loaded.

    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?

    Given no annotations, 0% schema description coverage, no output schema, and a sibling tool, the description is incomplete. It doesn't explain what '详细内容' (detailed content) includes, how results are structured, error conditions, or differentiation from 'get_all_dishes'. For a lookup tool with these contextual factors, the description should provide more guidance.

    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?

    Schema description coverage is 0%, so the description must compensate. The description mentions '菜品名称' (dish name) which maps to the 'dishName' parameter, but provides no additional semantic context about format, constraints, examples, or what constitutes a valid dish name. With 0% schema coverage and minimal parameter information in the description, this is inadequate.

    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 the sibling tool 'get_all_dishes', which appears to retrieve all dishes rather than specific dish details.

    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 the sibling tool 'get_all_dishes', nor any context about when this specific lookup tool is appropriate versus listing all dishes. Usage is implied (when you need details for a specific dish), but no explicit guidance is provided.

    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 the list is paginated, sorted, or filtered, or if there are rate limits or authentication requirements. 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, clear sentence that efficiently conveys the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to understand at a glance. There is no wasted text, and it earns its place by providing essential information concisely.

    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, no annotations), the description is adequate but has gaps. It explains what the tool does but lacks details on behavioral traits like response format or usage context. For a basic read operation, this might be minimally viable, but it could benefit from more completeness, such as mentioning the sibling tool or output specifics.

    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 beyond this, which is appropriate since there are no parameters to explain. In such cases, a baseline score of 4 is applied 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' and the resource 'all available dishes,' making the action and target explicit. However, it doesn't differentiate from the sibling tool 'get_dish_content,' which might retrieve detailed content of a specific dish, so it misses full sibling distinction.

    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 any context for choosing between them, such as whether this tool is for a high-level overview or the sibling for detailed information. Without such guidance, users must infer usage from the tool names alone.

    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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  • Evaluate tool definition quality.

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