xiaobenyang-mcp

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting a specific platform's trending data (e.g., 36氪热榜, B站热榜, 微博热搜). The descriptions are identical but the names unambiguously indicate different data sources, so there is no overlap or confusion between tools.
Naming Consistency5/5
All tools follow a perfectly consistent pattern: '实时数据/' prefix followed by the platform name and '热榜' (or '热搜' for 微博). The naming is uniform across all 17 tools, with no deviations in style or structure.
Tool Count4/5
With 17 tools, the count is slightly high but reasonable for covering multiple Chinese platform trends. It might feel heavy, but each tool corresponds to a distinct data source, so the number aligns well with the server's purpose of providing diverse real-time data.
Completeness5/5
The tool set comprehensively covers trending data from a wide range of major Chinese platforms (e.g., social media, news, tech sites). There are no obvious gaps for this domain—each tool provides access to a specific source, ensuring full coverage without dead ends.
Average 1.8/5 across 17 of 17 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior1/5
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 but offers none. It doesn't indicate whether this is a read-only operation, what data format it returns, whether it requires authentication, or any rate limits. The description is completely silent on behavioral characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise with just the tool name repeated, this represents under-specification rather than effective conciseness. The description fails to provide any useful information that would help an AI agent understand or use the tool, making it inefficient despite its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, no output schema, and the description's complete failure to explain what the tool does or how it differs from siblings, this is severely incomplete. For a tool in a crowded sibling space with no structured metadata, the description should provide substantial context but provides none.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so no parameter documentation is needed. The baseline for zero parameters is 4, as there's nothing for the description to compensate for regarding parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 its many siblings (e.g., 实时数据/微博热搜, 实时数据/知乎热榜). There's no indication of what differentiates this IT资讯热榜 from other hot lists, leaving users with no context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description fails to indicate whether this is a read or write operation, what data it returns, whether it requires authentication, any rate limits, or what format the output takes. For a tool with no annotation coverage, this represents a complete lack of behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (a single phrase), this represents under-specification rather than effective conciseness. The description fails to convey essential information about the tool's purpose and behavior. Every word should earn its place, but here the minimal content fails to serve its fundamental purpose of helping an AI agent understand and use the tool correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by the tool name (retrieving trending data from a major platform), the lack of annotations, and no output schema, the description is completely inadequate. It provides no information about what the tool returns, how the data is structured, or any behavioral characteristics. For a data retrieval tool with no structured metadata, this description fails to provide the minimal contextual information needed for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the baseline score is 4. The description doesn't need to compensate for any parameter documentation gaps, and the empty input schema is self-explanatory for a parameterless tool. No additional parameter information is provided or needed in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus alternatives. With 16 sibling tools all following the '实时数据/[platform]热榜' pattern, there is no indication of what makes this tool distinct, what context it's appropriate for, or when to choose it over similar tools like '实时数据/微博热搜' or '实时数据/抖音热榜'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, it fails to describe any behavioral traits such as whether this is a read-only operation, potential rate limits, authentication requirements, or what the tool returns (e.g., a list of trending topics). The description is essentially empty in terms of behavioral context, making it impossible for an agent to understand how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely concise (a single phrase), this brevity results in under-specification rather than effective conciseness. It does not front-load critical information or provide any structured details about the tool's functionality. The description fails to earn its place by adding value, making it inefficient despite its short length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (implied by being part of a '实时数据' or 'real-time data' family with many siblings) and the lack of annotations and output schema, the description is completely inadequate. It does not explain what the tool returns, how it interacts with the system, or any contextual nuances, leaving significant gaps for an agent to understand and use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100% (since there are no parameters to describe). In such cases, the baseline score is 4, as there is no need for the description to compensate for missing parameter information. The description does not add any parameter semantics, but this is acceptable given the absence of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It does not mention any specific context, prerequisites, or exclusions, nor does it reference sibling tools (e.g., '抖音热榜' vs. '微博热搜') to help differentiate usage scenarios. This leaves the agent with no information to make an informed selection among similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description offers zero behavioral information. It doesn't indicate whether this is a read-only operation, what kind of data it returns, whether there are rate limits, authentication requirements, or any other behavioral characteristics. The description carries the full burden of disclosure and completely fails to meet it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely brief, this represents under-specification rather than effective conciseness. The single phrase doesn't provide enough information to be useful, so it's not earning its place through efficient communication but rather through omission of necessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a data retrieval tool with no annotations, no output schema, and many similar sibling tools, the description is completely inadequate. It doesn't explain what data is returned, how it's formatted, what time period it covers, or how it differs from other hot list tools. The description fails to provide the minimal context needed for an agent to understand and use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100%, so there are no parameters to document. The baseline for zero parameters is 4, as there's no parameter information that needs to be conveyed beyond what the schema already indicates (no parameters).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance about when to use this tool versus its many sibling tools. With 16 similar-looking 'hot list' tools available, the description fails to indicate what makes the Sogou hot list unique or when it would be the appropriate choice among alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. However, it gives no information about what the tool does operationally—whether it fetches, streams, or processes data; its rate limits; authentication needs; or output format. The description is essentially empty, failing to convey any behavior beyond the tool's name, which is inadequate 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely concise (just the tool name repeated), this is not a virtue but under-specification. It lacks any structure or front-loaded information, failing to provide a purpose or usage context. Conciseness should not come at the cost of clarity; here, the brevity results in an ineffective description that does not help the agent understand the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by the tool name (likely involving real-time data from Baidu's hotlist), the description is completely inadequate. There are no annotations, no output schema, and the description adds no context about what the tool returns or how it behaves. For a data-fetching tool with many siblings, this leaves the agent without essential information to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema description coverage is 100% (since there are no parameters to describe). According to the rules, for zero parameters, the baseline score is 4. The description does not need to compensate for any parameter gaps, and it does not contradict the schema, so it meets the baseline requirement without adding extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or comparisons to sibling tools (e.g., use this for Baidu-specific trends vs. others for different platforms). Without any usage instructions, the agent has no basis for selecting this tool appropriately among the many similar hotlist tools available.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, the description offers no information about what the tool does (e.g., whether it retrieves, updates, or monitors data), its operational characteristics (e.g., rate limits, authentication needs), or expected outcomes. This leaves the agent completely in the dark about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely brief ('实时数据/36氪热榜'), this is not true conciseness but rather under-specification. It fails to convey essential information about the tool's function and usage, making it inefficient rather than succinct. The structure doesn't front-load critical details, as it provides no actionable content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
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 severely incomplete. It doesn't explain what the tool returns (e.g., a list of trending topics from 36Kr), how it behaves, or when to use it. For a tool in a family of similar '热榜' tools, this minimal description fails to provide the necessary context for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, meaning the schema fully documents the lack of inputs. The description doesn't add any parameter information, which is appropriate since there are no parameters to explain. This meets the baseline expectation for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 any specific context, prerequisites, or differences from sibling tools like '实时数据/微博热搜' or '实时数据/知乎热榜'. Without any usage instructions, the agent has no basis for selecting this tool over others in the same category.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description offers no information about what the tool returns (e.g., list format, data structure), whether it's a read-only operation, potential rate limits, authentication requirements, or any other behavioral traits. It's completely inadequate 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.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (only the tool name repeated), this is under-specification rather than effective brevity. The description fails to provide any meaningful information that would help an AI agent understand or use the tool. Every sentence should earn its place, but here there's essentially no content to evaluate for structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
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 completely inadequate. For a data retrieval tool (implied by the name), users need to know what data is returned, in what format, and any constraints. The description provides none of this essential context, making it impossible for an agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100% (though trivial since there are no parameters). With no parameters to document, the description doesn't need to compensate for any gaps. The baseline for zero parameters is 4, as there's no parameter information to provide beyond what's already clear from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With multiple sibling tools for different platforms (e.g., Weibo, Zhihu, Douyin), there's no indication of when Bilibili trending data would be appropriate versus other sources. No usage context, prerequisites, or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 but fails entirely. It doesn't indicate whether this is a read-only operation, if it requires authentication, what data format it returns, or any rate limits or constraints. The description adds no behavioral context beyond the name, making it impossible for an agent to understand how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—just the tool name repeated—but this is under-specification rather than effective brevity. It lacks any structure or front-loaded information, failing to communicate purpose or usage in a way that earns its place. While short, it doesn't achieve conciseness through clarity or efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by real-time data fetching and the lack of annotations and output schema, the description is completely inadequate. It doesn't explain what the tool returns (e.g., a list of hot searches, timestamps, rankings), how to interpret results, or any operational context. For a tool with no structured metadata, the description fails to provide essential information for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to compensate for any parameter gaps, and it doesn't add or detract from parameter understanding. A baseline score of 4 is appropriate as the absence of parameters means there's no burden on the description to explain them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus its siblings (e.g., other real-time data tools like '实时数据/知乎热榜' or '实时数据/抖音热榜'). It lacks any context about use cases, prerequisites, or distinctions from alternatives, leaving the agent with no information to make an informed selection among similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, the description offers no information about what the tool does, how it behaves, what data it returns, or any operational characteristics like rate limits, authentication needs, or data format. It completely fails to describe the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (just the tool name repeated), this represents under-specification rather than effective conciseness. The description fails to provide any meaningful information that would help an AI agent understand or use the tool, so it doesn't earn its place as a helpful description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations, no output schema, and a description that provides no meaningful information, this is completely inadequate. The description doesn't explain what the tool returns, how it differs from the '搜狗热榜' sibling, or any operational context. For a tool that presumably fetches real-time data, this level of documentation is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema description coverage, so the schema fully documents the parameter situation. The description doesn't need to compensate for any parameter gaps, and the baseline for zero parameters is 4. The description doesn't add parameter information, but that's acceptable given the parameterless design.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of context, prerequisites, or differentiation from the sibling '搜狗热榜' tool or other real-time data tools in the list. Users are left with no information about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 but offers none. It doesn't indicate whether this is a read operation, mutation, or other behavior; doesn't mention rate limits, authentication needs, or data format; and provides no insight into what '热榜' (hot list) entails (e.g., ranking criteria, update frequency). This leaves the agent completely in the dark about how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (just the tool name repeated), this is under-specification rather than effective brevity. The description fails to front-load critical information and doesn't use its limited space to add any value beyond what's already in the name. Every sentence should earn its place, but here there's essentially no meaningful content to evaluate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by '热榜' (hot list data) and the complete lack of annotations and output schema, the description is severely incomplete. It doesn't explain what data is returned, in what format, or with what limitations. For a data-fetching tool with no structured metadata, this description provides almost no useful context for an AI agent to understand or use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage (empty schema). Since there are no parameters to document, the description doesn't need to compensate for any gaps. The baseline for 0 parameters is 4, as the description appropriately doesn't waste space discussing non-existent parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus its many siblings (e.g., 实时数据/微博热搜, 实时数据/抖音热榜). There's no indication of context, prerequisites, or alternatives. The agent must guess based solely on the platform name (知乎) without any usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, it offers no information about the tool's behavior—such as whether it's read-only, requires authentication, has rate limits, returns real-time data, or involves any side effects. This leaves critical operational traits unspecified for a tool presumably fetching dynamic data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise but under-specified rather than efficiently informative. It consists only of the tool name repeated, which fails to provide meaningful content. While brevity is present, it lacks the necessary structure or front-loaded information to guide an agent effectively, making it more of a placeholder than a helpful description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (likely involving dynamic data fetching) and the absence of both annotations and an output schema, the description is severely incomplete. It doesn't explain what the tool returns, how it behaves, or any usage context, leaving the agent with insufficient information to understand or invoke the tool correctly in a real-world scenario.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to compensate for any parameter gaps, and it appropriately avoids unnecessary parameter details. A baseline score of 4 is applied since no parameter information is required, and the description doesn't misleadingly imply parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 any context, prerequisites, or differences from sibling tools like '实时数据/知乎热榜' or '实时数据/微博热搜', leaving the agent with no information about selection criteria or appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, the description offers no information about behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output might contain. It fails to describe any behavior beyond the implied action of accessing data, leaving significant gaps in understanding how the tool functions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting only of the tool name repeated. However, this under-specification is not a virtue of conciseness but a lack of necessary detail. It fails to front-load key information or provide any structured explanation, making it inefficient for helping an AI agent understand the tool's purpose and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by accessing real-time data from a news source, the description is incomplete. There are no annotations, no output schema, and the description lacks details on what the tool returns, how it behaves, or any usage context. For a tool that likely involves data retrieval and potential nuances like update frequency or data format, this minimal description is inadequate and fails to provide necessary context 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.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, meaning no parameters are documented because none exist. The description does not mention any parameters, which is appropriate since there are none to describe. It adds no semantic value beyond the schema, but given the baseline of 4 for zero parameters, this meets the standard without needing compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 its siblings. It does not mention any context, prerequisites, or alternatives. Given the list of sibling tools (e.g., '实时数据/微博热搜', '实时数据/知乎热榜'), there is no indication of when one might choose Tencent News over other news or social media hot lists, making it misleading due to the lack of differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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 but offers none. It doesn't indicate whether this is a read-only operation, if it requires authentication, has rate limits, or what the output might look like. The description is too vague to infer any behavioral traits, failing to compensate for the lack of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single phrase that restates the tool name, which is overly concise to the point of under-specification. While it lacks wasted words, it fails to provide any meaningful content, making it inefficient in conveying necessary information. Conciseness should not come at the cost of clarity, so this scores low for being too brief without substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by the tool name (likely fetching trending data from a specific source) and the lack of annotations and output schema, the description is severely incomplete. It doesn't explain what the tool does, how to use it, or what to expect in return. For a tool with no parameters but potential behavioral nuances, this description fails to provide the necessary context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the schema description coverage is 100%, meaning there are no parameters to document. The description doesn't need to add parameter semantics in this case. A baseline score of 4 is appropriate as the absence of parameters is adequately handled by the schema, and the description doesn't introduce confusion or unnecessary details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 its siblings, such as '实时数据/36氪热榜' or '实时数据/知乎热榜'. There is no mention of context, alternatives, or exclusions. This leaves the agent with no information to distinguish between similar tools, making it impossible to make an informed choice based on the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure, but it provides none. It doesn't indicate whether this is a read or write operation, what data format is returned, whether there are rate limits, authentication requirements, or any other behavioral characteristics. The description is completely silent on all operational aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While technically concise (it's just the tool name repeated), this represents under-specification rather than effective brevity. The description fails to provide any useful information that would help an AI agent understand or use the tool. Every sentence should earn its place, but here there's essentially no content to evaluate for structural effectiveness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a data retrieval tool (implied by '实时数据' and '热榜') with no annotations, no output schema, and a completely unhelpful description, the description is severely incomplete. The agent cannot understand what the tool returns, how to interpret results, or how it differs from similar tools. For a tool in a crowded sibling space with no structured metadata, this description provides inadequate context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters (schema description coverage is 100%), so there are no parameters requiring semantic explanation. The description doesn't need to compensate for any parameter documentation gaps. A baseline score of 4 is appropriate since the absence of parameters means there's no parameter semantics burden on the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides absolutely no guidance on when to use this tool versus its many siblings (e.g., 实时数据/微博热搜, 实时数据/知乎热榜). There's no indication of what makes '虎扑步行街热榜' distinct from other hot list tools, nor any context about when this specific platform's data would be needed. The agent receives zero usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description reveals nothing about what the tool actually does behaviorally—whether it fetches data, subscribes to updates, requires authentication, has rate limits, returns structured data, or has any side effects. It's completely inadequate for understanding the tool's operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely concise (just the tool name repeated), this is under-specification rather than effective conciseness. It doesn't front-load essential information about the tool's purpose or behavior. The single phrase doesn't earn its place by adding value beyond the name itself, making it inefficient for helping an AI agent understand the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity implied by real-time data fetching (typically involving network calls, potential authentication, and dynamic outputs) and the absence of both annotations and an output schema, the description is severely incomplete. It fails to explain what the tool returns, how it behaves, or any operational constraints, leaving critical gaps for an AI agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters (schema coverage is 100% with an empty object), so there are no parameters to document. The description doesn't need to compensate for any parameter gaps. A baseline score of 4 is appropriate since the schema fully covers the parameter situation (none exist), and the description doesn't contradict or add unnecessary information about parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 any specific context, prerequisites, or differences from sibling tools like '实时数据/虎扑步行街热榜' (which appears to be a similar tool without the 'A' suffix). There's no indication of when this tool is appropriate or when other tools should be used instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, it offers no information on traits such as read-only status, rate limits, authentication needs, or output format. This is inadequate for a tool that likely involves data retrieval, leaving the agent unaware of operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single phrase that mirrors the tool name, making it under-specified rather than concise. It lacks structure and fails to front-load essential information, such as purpose or usage. While brief, it does not earn its place by adding value beyond the name.
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 tool's likely complexity (fetching hot topics from a news source) and the absence of annotations and output schema, the description is incomplete. It does not explain what the tool returns, how data is structured, or any behavioral aspects, leaving significant gaps for the agent to understand its functionality.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so no parameter information is needed. The description does not add any parameter details, which is acceptable given the lack of inputs. This meets the baseline for tools without parameters, as it does not need to compensate for schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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 does not mention context, prerequisites, or comparisons to sibling tools like '实时数据/微博热搜' or '实时数据/知乎热榜'. This leaves the agent without direction on selection among similar hot-topic tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
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. However, it offers no information about traits such as whether this is a read-only operation, potential rate limits, authentication needs, data freshness, or output format. The description is too minimal to convey any behavioral context, leaving the agent with significant uncertainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—just the tool name repeated—but this is under-specification rather than effective brevity. It lacks any structured information or front-loaded details that would help an agent understand the tool's purpose. While it avoids verbosity, it fails to provide necessary context, making it inefficient for its intended use.
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 tool's complexity (likely a data-fetching operation with no parameters) and the absence of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a list of hot topics), how the data is structured, or any operational constraints. For a tool with no structured metadata, the description should compensate but does not.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the input schema has 100% description coverage (though empty). With no parameters to document, the description doesn't need to add parameter semantics. A baseline score of 4 is appropriate as the lack of parameters reduces the burden on the description, and it doesn't contradict or confuse the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
Tautological: description restates name/title.
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 context, prerequisites, or exclusions, and fails to differentiate from sibling tools like '实时数据/百度热榜' (which might be a broader Baidu hot list) or other platform-specific hot lists. Without any usage instructions, the agent must infer based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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