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xiaobenyang-com

bingcn

by xiaobenyang-com
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TypeScript

Server Quality Checklist

58%
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: bing_search performs keyword searches and returns a list of results with metadata, while fetch_webpage retrieves the full content of a specific webpage based on an ID. There is no overlap in functionality, making it easy for an agent to select the correct tool for each task.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern: bing_search and fetch_webpage. The names are descriptive, use snake_case uniformly, and clearly indicate the action (search/fetch) and target (bing/webpage), providing predictability across the tool set.

    Tool Count3/5

    With only 2 tools, the set feels thin for a search and content retrieval server, as it lacks operations like filtering, pagination, or advanced search options. While the tools cover basic workflows, the count is borderline low for the apparent scope, potentially limiting agent capabilities.

    Completeness3/5

    The tools provide core search and content retrieval functions, but there are notable gaps: no ability to update, delete, or manage search results, and no support for operations like caching or result refinement. The surface is functional but incomplete for robust web search and content handling.

  • Average 2.8/5 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 the full burden of behavioral disclosure. It only states what the tool does (fetch content) without any additional behavioral traits, such as whether it's read-only, requires authentication, has rate limits, or what the output format might be. For a tool with no annotations, 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.

    Conciseness4/5

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

    The description is concise and front-loaded in a single sentence: '根据提供的ID获取对应网页的内容'. It efficiently conveys the core purpose without unnecessary words. However, it could be slightly improved by adding minimal context, but it earns a high score for brevity and clarity within its limited scope.

    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 the complexity (a fetch operation with 1 parameter), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain the return values, error handling, or any behavioral aspects. For a tool that likely involves network calls or data retrieval, more context is needed to be fully helpful to an AI agent.

    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?

    The input schema has 1 parameter with 0% description coverage, and the description does not add any meaning beyond the schema. It mentions '提供的ID' (provided ID) but doesn't explain what 'result_id' represents, its format, or where it comes from. With low schema coverage, the description fails to compensate, leaving the parameter semantics unclear.

    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ID获取对应网页的内容' (fetch the content of a webpage based on the provided ID). It specifies the verb '获取' (fetch/get) and the resource '网页的内容' (webpage content), making the action explicit. However, it doesn't differentiate from the sibling tool 'bing_search', which likely serves a different purpose (searching vs. fetching by ID), so it doesn't reach the highest score.

    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 'bing_search' or any other context for usage, such as prerequisites or scenarios where this tool is preferred. The only implied usage is based on having a 'result_id', but this is not explicitly stated as a guideline.

    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 provided, the description carries full burden for behavioral disclosure. It mentions the return format (title, link, summary, ID) but doesn't address important behavioral aspects like rate limits, authentication requirements, result freshness, pagination, or error conditions. For a search tool with zero annotation coverage, this is insufficient.

    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 appropriately concise - a single sentence that states the action and return format. It's front-loaded with the core functionality. However, it could be slightly more structured by separating the action from the return details.

    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 search tool with 2 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain parameter usage, behavioral constraints, or provide enough context for the agent to use it effectively. The mention of return fields helps but doesn't compensate for the missing behavioral and parameter documentation.

    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 schema has 0% description coverage, so parameters are undocumented in the schema. The description mentions '指定的关键词' (specified keywords) which maps to the 'query' parameter, but doesn't explain the 'num_results' parameter at all. It adds minimal value beyond what's implied by the parameter names themselves.

    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: '使用必应搜索指定的关键词' (search specified keywords using Bing) and '返回搜索结果列表' (return search results list). It specifies the verb (search) and resource (Bing), but doesn't differentiate from the sibling tool 'fetch_webpage' which likely fetches specific webpages rather than performing searches.

    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 'fetch_webpage' or explain when to search versus fetch specific content. There's no context about appropriate use cases or limitations.

    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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