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 describes what content is returned but provides no information about rate limits, authentication needs, pagination, freshness of data, or error conditions. For a trending/news tool with zero annotation coverage, this leaves significant 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.

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

The description is a single, efficient Chinese sentence that front-loads the core purpose. Every clause adds value by specifying content domains and information types. No wasted words, though it could potentially benefit from structural separation of purpose from content details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's apparent simplicity (1 parameter, no output schema, no annotations), the description adequately covers what content is returned. However, it doesn't address the parameter's purpose, return format, or behavioral constraints that would be helpful for an AI agent. For a trending tool among many similar siblings, more contextual differentiation would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 1 parameter with 0% schema description coverage. The description doesn't mention any parameters at all, so it adds no semantic information beyond what the empty schema provides. However, with only one parameter and the tool appearing to be a simple fetch operation, the baseline of 3 is appropriate as the schema deficiency is minimal.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 36 氪热榜' (get 36Kr trending list) with specific content domains (entrepreneurship, business, tech) and types of information (investment/financing trends, emerging industry analysis, business model innovation). It distinguishes from siblings by specifying the 36Kr source, but doesn't explicitly differentiate content scope from similar news/trending tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 the 19 sibling tools (all news/trending/ranking tools). It doesn't mention alternatives, prerequisites, or specific contexts where 36Kr content would be preferred over other sources like BBC, NYTimes, or Weibo trending.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states the tool fetches news but doesn't disclose behavioral traits such as rate limits, authentication needs, data freshness, pagination, or output format. It mentions the content is in English ('英文资讯'), which is useful context, but overall lacks critical operational details for a news-fetching tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient sentence in Chinese that front-loads the core purpose ('获取 9to5Mac 苹果相关新闻') and lists specific content categories. Every part adds value without redundancy, making it appropriately sized and well-structured for a no-parameter tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is moderately complete. It clearly states what news is fetched and the language, but lacks details on behavior, output format, and usage context. For a simple news retrieval tool, this is adequate but has gaps in operational transparency.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for zero-parameter tools. It appropriately focuses on the tool's function without unnecessary parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 9to5Mac 苹果相关新闻' (get 9to5Mac Apple-related news) with specific content categories like product releases, iOS updates, Mac hardware, app recommendations, and company news. It distinguishes from siblings by specifying the source (9to5Mac) and topic (Apple), but doesn't explicitly contrast with other news tools beyond the name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 when to choose 9to5Mac over other news sources like BBC, NYTimes, or TheVerge, or any prerequisites or exclusions. Usage is implied by the topic 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions what content is available but lacks behavioral details such as rate limits, authentication needs, data freshness, pagination, or error handling. The description doesn't contradict annotations (none exist).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient sentence in Chinese that front-loads the core purpose and lists content areas. It's appropriately sized with no wasted words, though it could be more structured for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 2 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It covers the tool's purpose and content scope but lacks details on parameters, return values, behavioral traits, and usage context, making it inadequate for effective tool selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 for two undocumented parameters (category, edition). It lists content categories but doesn't explain how they map to the 'category' parameter or what 'edition' controls. The description adds some meaning but doesn't fully clarify parameter usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 BBC 新闻' (get BBC news) with specific content areas listed (global news, UK news, business, politics, health, education, technology, entertainment). It distinguishes from siblings by specifying BBC as the source, but doesn't explicitly contrast functionality differences beyond the source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives is provided. The description lists content areas but doesn't specify use cases, prerequisites, or comparisons to sibling tools like get-nytimes-news or get-theverge-news.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what data is retrieved (Bilibili video rankings across sections) and hints at its cultural relevance, but lacks critical details: whether it's a read-only operation, any rate limits, authentication requirements, pagination behavior, or what the return format looks like (especially since there's no output schema). For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is appropriately concise—one sentence that efficiently states the core functionality (getting Bilibili rankings) and adds context about section diversity and cultural relevance. It's front-loaded with the main purpose, though the second clause about 'reflecting youth trends' could be seen as slightly extraneous but still adds value. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (a ranking tool with one parameter but no schema documentation), no annotations, and no output schema, the description is incomplete. It covers the 'what' (Bilibili video rankings) but misses the 'how': parameter usage, return format, behavioral constraints (e.g., is it safe to call frequently?), and differentiation from sibling tools. For a tool in a server with many similar trending/ranking tools, more contextual guidance is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter ('type') with 0% description coverage (no schema documentation). The tool description provides no information about parameters—it doesn't mention the 'type' parameter at all, nor explain what values it accepts (e.g., whether it corresponds to the mentioned sections like '动画' or '音乐'). With low schema coverage and no compensation in the description, users are left guessing about parameter usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取哔哩哔哩视频排行榜' (get Bilibili video rankings) with specific resources mentioned (全站、动画、音乐、游戏等多个分区的热门视频 - popular videos from various sections like all-site, animation, music, games). It distinguishes from siblings by focusing on Bilibili rankings rather than other platforms like Douban, Weibo, or news sources. However, it doesn't explicitly contrast with similar ranking tools (e.g., get-douban-rank) beyond the platform difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. While it mentions '反映当下年轻人的内容消费趋势' (reflects current youth content consumption trends), this is more about the data's nature than usage context. There's no indication of when to choose this over other ranking/trending tools (e.g., get-douyin-trending for short videos, get-zhihu-trending for Q&A), nor any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions '实时热门榜单' (real-time hot rankings) which implies dynamic data, but doesn't specify update frequency, rate limits, authentication needs, or what 'real-time' means. It also doesn't describe the return format (e.g., list structure, pagination) or error conditions. For a tool with no annotation coverage, this leaves significant 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.

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

The description is appropriately concise—one sentence that efficiently states the tool's purpose and scope. It's front-loaded with the core function ('获取豆瓣实时热门榜单') and adds useful details without redundancy. Every part of the sentence contributes value, making it well-structured for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (3 parameters, no annotations, no output schema), the description is incomplete. It covers the basic purpose but lacks parameter explanations, behavioral details (e.g., data freshness, limitations), and output information. For a ranking tool with multiple parameters and no structured support, the description should provide more context to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 for undocumented parameters. It mentions no parameters at all, leaving all three parameters (type, start, count) unexplained. The description doesn't add any meaning beyond what the bare schema provides (e.g., what 'type' controls, what 'start' and 'count' do for pagination). With low coverage and no parameter info in the description, this falls below the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取豆瓣实时热门榜单' (get Douban real-time hot rankings) with specific resources mentioned (books, movies, TV shows, variety shows) and data included (ratings and popularity). It distinguishes itself from siblings by focusing on Douban content rather than other platforms like Weibo, Zhihu, or news sites. However, it doesn't explicitly contrast with similar ranking tools like get-bilibili-rank or get-smzdm-rank beyond the platform difference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 any prerequisites, limitations, or comparison with sibling tools (e.g., use this for Douban content vs. get-weibo-trending for social media trends). The context is implied (real-time hot rankings) but lacks explicit usage instructions or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states what data is returned but doesn't disclose behavioral aspects like whether this is a real-time feed, historical data, rate limits, authentication requirements, data freshness, or format of results. For a trending tool with zero 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.

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

The description is a single, efficient sentence that clearly states the tool's purpose and scope. It's appropriately sized for a simple trending data tool with no parameters. Every word contributes to understanding what the tool provides.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a trending data tool with no annotations and no output schema, the description is insufficient. It doesn't explain what format the trending data returns (list of items, timestamps, metrics), how results are structured, whether there's pagination, or what time period the '当下' (current moment) refers to. The description should provide more context about the output.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters since none exist. It focuses on what the tool returns rather than inputs, which is correct for a parameterless tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取抖音热搜榜单' (get Douyin trending list) with specific content scope ('社会话题、娱乐事件、网络热点和流行趋势' - social topics, entertainment events, internet hotspots, and trending topics). It distinguishes from siblings by specifying the Douyin platform, but doesn't explicitly differentiate functionality beyond platform source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention when this tool is appropriate, what prerequisites exist, or how it differs from similar trending tools like get-weibo-trending or get-toutiao-trending beyond the platform name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 only states what content is retrieved without mentioning how (e.g., latest articles, trending content, pagination), frequency limits, authentication needs, or response format. For a tool with zero annotation coverage, this leaves significant 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.

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

The description is a single, efficient sentence that directly states the tool's purpose and content scope without unnecessary words. Every element (source, content types, depth) contributes meaningfully.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema), the description adequately covers the basic purpose and content scope. However, without annotations or output schema, it should ideally provide more behavioral context about what exactly is returned (e.g., list of articles with metadata) to be fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on the content scope.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取机核网游戏相关资讯' (get Gcores gaming-related information) with specific content types listed (game reviews, player culture, game development, gaming peripherals). It distinguishes from siblings by specifying the Gcores source and gaming focus, though it doesn't explicitly contrast with other news/tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 what makes Gcores unique compared to other gaming/news sources in the sibling list, nor does it specify use cases or prerequisites for accessing this content.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states what content is retrieved without mentioning any behavioral traits like rate limits, authentication needs, pagination behavior, or response format. For a tool with parameters and no output schema, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It wastes no words but could be slightly more structured by separating content types, though this doesn't significantly hinder clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (2 parameters, no annotations, no output schema), the description is incomplete. It lacks details on parameter usage, behavioral constraints, and output format, making it inadequate for an agent to reliably invoke the tool without additional context or trial-and-error.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no information about the parameters (limit and offset) beyond what the schema provides. With 0% schema description coverage and two parameters, the description fails to compensate by explaining their purpose, such as pagination or result limiting, leaving the agent to guess based on generic parameter names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取爱范儿科技快讯' (get ifanr tech news) with specific content details like '最新的科技产品、数码设备、互联网动态等前沿科技资讯' (latest tech products, digital devices, internet trends, and cutting-edge tech information). It distinguishes from siblings by specifying the source (ifanr) and content focus, though it doesn't explicitly contrast with other news tools beyond the name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 any specific scenarios, prerequisites, or comparisons with sibling tools like get-36kr-trending or get-theverge-news, leaving the agent to infer usage based on the source name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions content types but lacks behavioral details like whether it returns latest articles, trending topics, or paginated results; rate limits; authentication needs; or data freshness. The description is vague on operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient sentence in Chinese that front-loads the main purpose and lists content areas. It's appropriately sized with no wasted words, though it could be slightly more structured for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and low parameter coverage, the description is incomplete. It covers what content is fetched but misses key details like return format (e.g., list of articles), error handling, or usage constraints, leaving gaps for effective tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter 'region' with 0% description coverage, and the tool description provides no information about parameters. It doesn't explain what 'region' means (e.g., geographic filtering for news) or its optional nature, failing to compensate for the low schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as '获取 InfoQ 技术资讯' (get InfoQ tech news), specifying the resource (InfoQ) and content scope (software development, architecture design, cloud computing, AI, enterprise tech, and developer trends). It distinguishes from siblings by focusing on InfoQ specifically, though it doesn't explicitly contrast with other news sources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. With many sibling tools for different news sources (e.g., get-bbc-news, get-nytimes-news), it lacks explicit context for choosing InfoQ over others, such as for Chinese tech news or specific topics like enterprise software.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions the tool retrieves rankings of '高质量中文技术文章和教程' (high-quality Chinese technical articles and tutorials), which implies a read-only operation, but doesn't specify whether it requires authentication, rate limits, pagination, freshness of data, or what the output format looks like. For a tool with zero annotation coverage, this leaves significant 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.

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

The description is appropriately concise with a single sentence that front-loads the core purpose ('获取掘金文章榜' - get Juejin article rankings). It efficiently adds context about content types and domains without unnecessary elaboration. However, it could be slightly more structured by separating purpose from details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (1 parameter, no annotations, no output schema), the description is incomplete. It covers the purpose and content scope but misses critical details: parameter usage, behavioral traits (e.g., authentication needs, rate limits), and output expectations. For a tool with no structured support, the description should provide more comprehensive guidance to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter ('category_id') with 0% description coverage, and the tool description provides no information about parameters. The description doesn't mention what 'category_id' is, how to use it, or whether it's optional/required. With low schema coverage, the description fails to compensate, leaving the parameter undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取掘金文章榜' (get Juejin article rankings) with specific resources mentioned ('高质量中文技术文章和教程' - high-quality Chinese technical articles and tutorials) and domains covered ('前端开发、后端技术、人工智能、移动开发及技术架构等领域' - front-end development, back-end technology, AI, mobile development, and technical architecture). It distinguishes from siblings by specifying Juejin as the source, but doesn't explicitly contrast with similar tools like 'get-zhihu-trending' which might also provide Chinese content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 when to choose Juejin articles over other sources like Zhihu or Weibo trending, nor does it specify prerequisites, timing considerations, or exclusions. The context is implied (getting Chinese technical articles from Juejin), but lacks explicit usage instructions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions the content scope but doesn't disclose behavioral traits like whether this is a read-only operation, rate limits, authentication needs, data freshness, or format of returned data. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient Chinese sentence that directly states the tool's function and content scope. Every word contributes meaning without redundancy, making it appropriately front-loaded and concise for a simple data retrieval tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a parameterless tool with no output schema, the description provides adequate basic context about what content to expect. However, it lacks details about return format, data structure, or limitations that would help an agent use it effectively. The completeness is minimal but acceptable for this complexity level.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description appropriately doesn't discuss parameters, maintaining focus on what the tool does rather than inputs it accepts. This meets the baseline expectation for parameterless tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取网易新闻热点榜' (get NetEase News trending list) with specific content categories listed. It distinguishes from siblings by specifying the source (NetEase News) and content type (Chinese news), though it doesn't explicitly contrast with similar tools like get-tencent-news-trending.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. With multiple news/trending tools in the sibling list (e.g., get-tencent-news-trending, get-thepaper-trending), there's no indication of when NetEase News is preferred over other Chinese news sources or general trending tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 content categories and language options but lacks critical information: whether this is a search/filtering tool or returns trending/current news, pagination/rate limits, authentication requirements, freshness of data, or what the output format looks like. The description provides some context about content scope but misses key behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient Chinese sentence that packs substantial information about content scope and language options. It's appropriately sized and front-loaded with the core purpose. However, it could be slightly more structured by separating purpose from content details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a news retrieval tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It covers content scope and language but misses parameter explanations, behavioral context (how news is retrieved/filtered), and output expectations. Given the complexity and lack of structured data, the description should do more.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% (both parameters have no descriptions in schema). The description doesn't mention any parameters at all - it doesn't explain what 'region' or 'section' parameters do, their possible values, or how they affect the news retrieval. With 2 undocumented parameters and no compensation in the description, this is inadequate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取纽约时报新闻' (get New York Times news) with specific content categories (international politics, economic finance, social culture, science technology, art reviews) and language options (high-quality English or Chinese international news). It distinguishes from siblings by specifying the New York Times source, but doesn't explicitly contrast with other news tools like get-bbc-news or get-theverge-news.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description mentions content categories and languages, but doesn't specify scenarios where New York Times news would be preferred over BBC, The Verge, or other news sources in the sibling list. No exclusions or prerequisites are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 describes what content types are included but doesn't mention how results are returned (format, pagination, rate limits), whether it's a read-only operation, or any authentication requirements. For a tool with no annotation coverage, this leaves significant 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.

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

The description is a single, efficient sentence that front-loads the core purpose ('获取什么值得买热门') followed by specific content details. There's no wasted text, though it could be slightly more structured for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no annotations, no output schema, and 0% parameter schema coverage, the description is incomplete. While it clearly states what content is fetched, it doesn't address how results are structured, what the parameter does, or any operational constraints. For a tool in this context, more information is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description provides zero information about the 'unit' parameter. With 0% schema description coverage and no parameter details in the description, the agent has no guidance on what this parameter means, what values it accepts, or whether it's required. This is inadequate for a tool with one parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取什么值得买热门' (get SMZDM trending/hot content) followed by a detailed list of content types (product recommendations, discount info, shopping guides, product reviews, consumer experience sharing). It specifies the resource (SMZDM platform) and content scope, though it doesn't explicitly differentiate from sibling tools beyond the platform name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 any specific use cases, prerequisites, or comparisons to sibling tools that fetch trending content from other platforms (like get-zhihu-trending or get-weibo-trending). The agent must infer usage from the platform name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool fetches a '热榜' (hot ranking), implying a read-only operation that returns trending content, but lacks details on rate limits, authentication needs, data freshness, pagination, error handling, or output format. For a tool with no annotation coverage, this leaves significant 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.

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

The description is a single, efficient sentence that front-loads the core action ('获取少数派热榜') and elaborates with content details. It avoids redundancy and wastes no words, though it could be slightly more structured by separating purpose from context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, no annotations, no output schema), the description is incomplete. It adequately states the purpose but lacks usage guidelines, parameter semantics, and behavioral details needed for an AI agent to invoke it correctly without guesswork. The absence of an output schema further increases the need for more descriptive context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must compensate for two undocumented parameters ('tag' and 'limit'). It adds no information about these parameters—not explaining what 'tag' filters (e.g., content categories), what 'limit' controls (e.g., number of items), or their default behaviors. This fails to address the schema's lack of descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as '获取少数派热榜' (get SSPAI ranking), specifying it retrieves a ranking of content from the Chinese tech/lifestyle platform SSPAI. It distinguishes from siblings by mentioning the specific source (SSPAI) and content types (digital product reviews, software recommendations, lifestyle guides, efficiency tips), but doesn't explicitly contrast with similar tools like 'get-smzdm-rank' or 'get-zhihu-trending' beyond the source name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 when SSPAI content is preferred over other Chinese tech sources (e.g., vs. 'get-smzdm-rank' for deals or 'get-zhihu-trending' for Q&A), nor does it specify any prerequisites, exclusions, or contextual triggers for selection among the many sibling tools listed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions the content categories but doesn't disclose important behavioral aspects: whether this is a read-only operation, how frequently data updates, whether authentication is required, rate limits, pagination behavior (implied by page_size parameter but not explained), or what format/quantity of data is returned. For a tool with no annotation coverage, this leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is appropriately concise - a single Chinese sentence that efficiently communicates the core functionality and content scope. It's front-loaded with the main purpose and doesn't contain redundant information. However, it could be slightly more structured by separating purpose from content details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no annotations, no output schema, and 0% schema description coverage for its parameter, the description is insufficiently complete. It covers what content is retrieved but misses critical context about how to use the parameter, what the return format looks like, behavioral constraints, and differentiation from similar tools. For a trending news fetcher with one parameter, more guidance is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 for the undocumented parameter. The description mentions nothing about the 'page_size' parameter - its purpose, typical values, default behavior, or how it affects results. With one parameter completely undocumented in both schema and description, this represents a significant gap in parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取腾讯新闻热点榜' (get Tencent News trending list) with specific content categories including domestic/international news, social hotspots, financial information, entertainment, and sports. It distinguishes from siblings by specifying the source (Tencent News) and Chinese-language focus, though it doesn't explicitly contrast with similar tools like get-netease-news-trending or get-toutiao-trending.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. With 19 sibling tools that appear to fetch trending content from different sources (BBC, NYTimes, Weibo, Zhihu, etc.), there's no indication of when Tencent News would be preferred over other Chinese news sources like NetEase or Toutiao, or when to use this versus general news aggregators.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions the content categories (时政要闻, 财经动态, etc.) which gives some behavioral context about what types of news to expect, but doesn't disclose important traits like whether this is a read-only operation, rate limits, authentication needs, response format, or freshness of data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient sentence that front-loads the core purpose ('获取澎湃新闻热榜') followed by additional context about content categories. Every word earns its place with no redundancy or wasted space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read operation with no parameters and no output schema, the description provides adequate basic information about what the tool does and what content to expect. However, without annotations and with no output schema, it should ideally mention something about the return format or structure of the trending list data to be more complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0 parameters and 100% schema description coverage, the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema already fully documents this. No additional parameter information is needed or provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取澎湃新闻热榜' (get ThePaper trending list) with specific content categories listed. It distinguishes itself from siblings by specifying the source (澎湃新闻/ThePaper) and content type (热榜/trending list), though it doesn't explicitly contrast with similar tools like get-zhihu-trending or get-weibo-trending.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention when this tool is appropriate compared to other trending/news tools in the sibling list, nor does it specify any prerequisites or context for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states what content is retrieved but doesn't disclose behavioral traits: no information about rate limits, authentication needs, freshness of data, pagination, format of returned content, or whether this is a read-only operation. The description is purely about content scope without operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient Chinese sentence that front-loads the core purpose ('获取 The Verge 新闻') followed by content scope details. Every word contributes to understanding what the tool provides, with zero redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 no parameters, the description is incomplete. It covers content scope but lacks crucial operational context: what format the news is returned in (articles, headlines, summaries), how many items, freshness, whether it's trending vs recent, or any error conditions. 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, and the schema fully documents the empty parameter set.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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 The Verge 新闻' (get The Verge news) with specific content areas listed (科技创新, 数码产品评测, 互联网趋势, 科技公司动态). It distinguishes from siblings by specifying The Verge as the source, but doesn't explicitly contrast with other news tools like get-nytimes-news or get-bbc-news beyond the source name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. With 19 sibling tools including other news sources (BBC, NYTimes) and content types (trending, rank), there's no indication of when The Verge content is preferred or what differentiates it from other English tech news sources like 9to5mac-news.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states what content is retrieved. It doesn't disclose behavioral traits like rate limits, authentication needs, freshness of data, pagination, or error handling. The description is functional but lacks operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient Chinese sentence that directly states the tool's function and content scope. It's front-loaded with the core purpose and adds useful detail about content domains without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no annotations and no output schema, the description adequately explains what the tool does but lacks completeness regarding behavioral context. It doesn't describe the return format, data structure, or any limitations, which would be helpful given the absence of structured metadata.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing on the tool's purpose instead. Baseline is 4 for zero-parameter tools.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取今日头条热榜' (get Toutiao trending list) with specific content domains listed (politics, social events, international news, tech, entertainment). It distinguishes from siblings by specifying the source (Toutiao) and content type (Chinese news), but doesn't explicitly contrast with similar tools like get-tencent-news-trending.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives is provided. The description mentions content domains but doesn't specify use cases, prerequisites, or comparisons with sibling tools like get-weibo-trending or get-zhihu-trending for different Chinese platforms.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 '实时热门中文资讯' (real-time trending Chinese information) which implies freshness, but doesn't disclose important behavioral traits like rate limits, authentication requirements, data format, pagination, or whether this is a read-only operation. The description is insufficient for a tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is a single, efficient sentence that front-loads the core purpose ('获取微博热搜榜') and then elaborates with content categories. Every element earns its place by specifying the platform, content types, and real-time nature. It could be slightly more structured but is appropriately concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no annotations, no output schema), the description is adequate but has clear gaps. It explains what content is returned but doesn't describe the return format, data structure, or any limitations. For a trending data tool, more information about the output would be helpful, though the lack of output schema increases the burden on the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and schema description coverage is 100% (empty schema). The description doesn't need to explain any parameters, and the baseline for zero parameters is 4. The description appropriately focuses on what the tool returns rather than input parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取微博热搜榜' (get Weibo trending list) with specific content categories like current affairs, social phenomena, entertainment news, celebrity updates, and trending topics. It distinguishes itself from siblings by specifying the Weibo platform and Chinese-language content, but doesn't explicitly contrast with similar tools like get-douyin-trending or get-zhihu-trending.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. While it mentions '微博热搜榜' (Weibo trending list), it doesn't explain when to choose Weibo trending over other Chinese social media trending tools like get-douyin-trending or get-zhihu-trending, nor does it mention any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. While it describes what data is returned (reading data and ranking information), it doesn't disclose important behavioral traits: whether this is a read-only operation, rate limits, authentication requirements, data freshness, pagination, or error conditions. For a ranking 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.

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

The description is a single, efficient Chinese sentence that communicates the core purpose. It's appropriately sized for a simple ranking tool, though it could be more front-loaded with the most critical information about the optional category parameter.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and a parameter with 0% schema coverage, the description is incomplete. It doesn't explain the category parameter, return format, or behavioral constraints. For a tool that presumably returns structured ranking data, more context about what information is returned and how to use the optional filtering would be helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 1 parameter (category) with 0% description coverage. The tool description provides no information about this parameter - it doesn't mention categories at all, what values are accepted, or how filtering by category works. With low schema coverage, the description fails to compensate for the undocumented parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取微信读书排行榜' (get WeChat Reading rankings) with specific resources mentioned (popular novels, bestsellers, new book recommendations, literary works). It distinguishes from siblings by specifying the WeChat Reading platform, but doesn't explicitly differentiate from other ranking tools like get-douban-rank or get-bilibili-rank beyond the platform name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. With 20 sibling tools including other ranking/trending tools (get-douban-rank, get-bilibili-rank, get-smzdm-rank, etc.), there's no indication of when this specific WeChat Reading ranking tool is appropriate versus other ranking tools or news/trending tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 describes what the tool does (retrieves trending content) but doesn't mention any behavioral traits like whether it's a read-only operation, rate limits, authentication needs, data freshness, or what the output format looks like. 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.

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

The description is a single, well-structured sentence that efficiently conveys the tool's purpose and scope. It's appropriately sized and front-loaded with the core function, though it could potentially be more concise by removing some of the domain examples if they're redundant with '多领域' (multiple domains).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (retrieving trending content from a specific platform), no annotations, no output schema, and incomplete parameter documentation (0% coverage), the description is insufficient. It explains what the tool does but lacks crucial details about behavior, output format, and parameter usage, making it incomplete for effective agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 1 parameter (limit) with 0% description coverage, and the tool description doesn't mention any parameters. With low schema coverage (<50%), the description doesn't compensate by explaining the parameter's purpose or usage. However, since there's only one parameter and it's optional (0 required parameters), the baseline is slightly higher than if there were multiple undocumented parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '获取知乎热榜' (get Zhihu trending) with specific details about the content it retrieves - '包含时事热点、社会话题、科技动态、娱乐八卦等多领域的热门问答和讨论的中文资讯' (includes Chinese information on trending Q&A and discussions across multiple domains like current events, social topics, tech trends, entertainment gossip). It distinguishes itself from siblings by specifying the Zhihu platform and the type of content (trending Q&A/discussions).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by mentioning the specific platform (Zhihu) and content type (trending Q&A/discussions in Chinese), which helps differentiate it from siblings that target other platforms like Weibo, Douyin, or news sources. However, it doesn't explicitly state when to use this tool versus alternatives or provide any exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.