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 what the tool does but doesn't describe behavioral traits like whether it's read-only (implied by '获取' but not explicit), rate limits, authentication needs, error conditions, or what the return format looks like (especially important since there's no output schema). For a tool with no annotations, 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 directly states the tool's purpose. It's appropriately sized for a simple tool with two parameters. There's no wasted verbiage, and it's front-loaded with the core functionality.

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 (simple retrieval), lack of annotations, and absence of an output schema, the description is incomplete. It doesn't explain what the return value contains (e.g., list of posts with fields like text, timestamp, likes), error handling, or behavioral constraints. For a tool with no structured output documentation, the description should provide more context about what to expect.

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 100%, with both parameters (uid and limit) well-documented in the schema. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain uid format or limit constraints). With high schema coverage, the baseline is 3, and the description doesn't compensate with extra semantic context.

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 action ('获取' - get/retrieve) and resource ('微博用户的最新动态和帖子' - latest activities and posts of a Weibo user). It specifies the scope ('指定微博用户' - specified Weibo user) and what is retrieved ('最新动态和帖子' - latest activities and posts). However, it doesn't explicitly differentiate from sibling tools like get_profile (which might get user profile info) or search_content (which might search across 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 prefer get_feeds over get_profile (for user info), search_content (for content search), or get_hot_search (for trending topics). There's no context about use cases, 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. While it indicates this is a read operation ('获取' - get), it doesn't describe important behavioral traits such as rate limits, authentication requirements, data freshness (how current is '当前' - current), pagination, or error conditions. The description is minimal and 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 sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool with one parameter, though it could be slightly more informative without losing conciseness.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the return value looks like (e.g., list structure, fields like topic names and metrics), nor does it cover behavioral aspects like rate limits or authentication. For a tool that likely interacts with an external API (Weibo), more context is needed for 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?

The schema description coverage is 100%, with the single parameter 'limit' fully documented in the schema ('返回的最大热搜条目数量' - maximum number of hot search entries to return). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high 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: '获取当前微博热搜榜的热门话题列表' (Get the current list of hot topics from Weibo's hot search ranking). It specifies the verb ('获取' - get) and resource ('微博热搜榜的热门话题列表' - Weibo hot search ranking topic list). However, it doesn't differentiate from sibling tools like 'search_content' or 'search_users' which might also retrieve content from Weibo.

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 this tool is appropriate (e.g., for trending topics vs. general content search) or when to use sibling tools like 'search_content' instead. There's no context about exclusions or prerequisites.

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 retrieves detailed profile information but doesn't specify aspects like whether it's read-only, requires authentication, has rate limits, or what format the output takes. This leaves significant gaps in understanding the tool's behavior beyond its basic purpose.

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, clear sentence that directly states the tool's purpose without any unnecessary words or fluff. It's front-loaded with the essential information, making it highly efficient and easy to understand at a glance.

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 lack of annotations and output schema, the description is incomplete. It doesn't address behavioral traits like safety, authentication needs, or output format, which are crucial for a tool that likely involves external API calls. For a tool with no structured metadata, the description should provide more context 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 100% description coverage, with the 'uid' parameter clearly documented as '微博用户的唯一标识符' (Weibo user's unique identifier). The description doesn't add any additional parameter details beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without extra value.

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 action ('获取' meaning 'get') and the resource ('微博用户的详细资料信息' meaning 'detailed profile information of a Weibo user'). It specifies what the tool does without being tautological. However, it doesn't explicitly differentiate from sibling tools like 'search_users', which might also retrieve user information but with different scopes or methods.

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, context, or comparisons to sibling tools such as 'search_users', leaving the agent to infer usage based solely on the tool name and description without explicit direction.

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 searching and returning posts but fails to describe key behaviors: whether results are paginated (implied by 'page' parameter but not explained), authentication requirements, rate limits, error handling, or the format of returned data. For a search tool with no annotation coverage, this leaves significant gaps in understanding its operation.

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 function without unnecessary words. It is front-loaded with the core action ('搜索微博内容') and outcome ('返回相关的微博帖子'), making it easy to parse. Every part of the sentence contributes to understanding the tool's purpose.

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 of a search operation, lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects like pagination, authentication, or result format, which are critical for effective tool use. The schema handles parameters well, but the overall context for invocation and interpretation of results is insufficient.

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 100%, with clear descriptions for 'keyword', 'limit', and 'page' parameters. The description adds no additional semantic information beyond what the schema provides (e.g., it doesn't explain keyword matching logic, default values beyond 'page', or result ordering). Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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: '根据关键词搜索微博内容并返回相关的微博帖子' (Search Weibo content by keyword and return relevant Weibo posts). It specifies the verb '搜索' (search) and resource '微博内容' (Weibo content), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'search_users' or 'get_feeds', which prevents a perfect score.

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 sibling tools like 'search_users' (for user searches) or 'get_feeds' (for feed retrieval), nor does it specify scenarios where this tool is preferred or excluded. Without such context, the agent lacks clear usage direction.

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 mentions the action ('搜索' - search) and outcome ('返回匹配的用户列表' - return matching user list), but doesn't describe important behavioral traits like whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or what fields are included in the returned user list. 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.

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

The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized for a simple search tool. However, it could be slightly more front-loaded by explicitly mentioning it's for Weibo users earlier in the sentence, but this is a minor issue.

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 (search operation with 2 parameters), no annotations, and no output schema, the description is minimally adequate. It explains what the tool does but lacks important context about behavioral characteristics, usage guidelines, and output format. The description doesn't compensate for the absence of annotations and output schema, making it incomplete for optimal agent understanding.

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 100%, with both parameters ('keyword' and 'limit') having clear descriptions in the schema. The description adds no additional parameter semantics beyond what's already documented in the schema. According to the scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no parameter information in the description.

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: '根据关键词搜索微博用户并返回匹配的用户列表' (Search Weibo users by keyword and return matching user list). It specifies the verb ('搜索' - search), resource ('微博用户' - Weibo users), and outcome ('返回匹配的用户列表' - return matching user list). However, it doesn't explicitly differentiate from sibling tools like 'search_content' or 'get_profile', which prevents a perfect score.

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 this tool is appropriate compared to sibling tools like 'search_content' (which might search posts instead of users) or 'get_profile' (which might retrieve specific user details). There's no context about use cases, prerequisites, or exclusions.

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