Qiniu MCP Server

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by qiniu

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
The tool set has clear separation between CDN, object storage, image processing, and live streaming domains, but within domains there is some overlap. For example, image_scale_by_percent and image_scale_by_size have very similar purposes, and get_object vs get_object_url could be confusing. The live streaming tools are well-differentiated from other domains.
Naming Consistency4/5
Most tools follow a consistent snake_case pattern with descriptive names. The live streaming tools have a clear 'live_streaming_' prefix convention. Minor inconsistencies exist: 'cdn_prefetch_urls' and 'cdn_refresh' don't follow the same prefix pattern as live streaming tools, and 'version' is a single word rather than descriptive.
Tool Count3/5
22 tools is borderline high for a single server, especially since it covers multiple distinct domains (CDN, object storage, image processing, live streaming). While each domain might justify its own tool count, bundling them together creates a somewhat heavy interface. The count feels more like 4 separate servers combined into one.
Completeness4/5
For each covered domain, the tool set provides good coverage. Object storage has upload, list, and get operations; image processing has multiple transformation tools; live streaming has comprehensive bucket and stream management. Minor gaps include no object deletion or update operations, and CDN tools are limited to prefetch/refresh without broader configuration options.
Average 3.1/5 across 22 of 22 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 2 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on November 27, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
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.
Add a glama.json file to provide metadata about your server.
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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.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions returning a bucket based on conditions, but fails to specify key behaviors such as whether this is a read-only operation, what authentication is needed, if there are rate limits, or what the output format looks like. This leaves significant gaps in understanding 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it is under-specified and lacks clarity. While it avoids unnecessary length, the sentence does not effectively communicate purpose or usage, making it inefficient rather than truly concise. It could be more front-loaded with specific information.
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 (a list operation with filtering), lack of annotations, and no output schema, the description is incomplete. It does not explain what is returned (e.g., bucket details, list format), authentication requirements, or error handling. This leaves the agent with insufficient context to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'prefix' parameter clearly documented in the schema. The description adds no additional meaning beyond what the schema provides—it vaguely refers to 'conditions' but does not elaborate on parameters. With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate but also does not detract.
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?
The description 'Return the Bucket you configured based on the conditions' is vague and tautological—it essentially restates the tool name 'list_buckets' without specifying what 'configured' means or what 'conditions' entail. It does not clearly distinguish this tool from sibling tools like 'list_objects' or 'live_streaming_list_buckets', leaving the purpose ambiguous.
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?
No guidance is provided on when to use this tool versus alternatives. For example, it does not explain when to choose 'list_buckets' over 'list_objects' or 'live_streaming_list_buckets', nor does it mention any prerequisites or context for usage. The description lacks explicit or implied usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the CDN 'automatically triggers the prefetch process' and stores resources 'in advance,' which implies a write/mutation operation, but doesn't disclose behavioral traits like rate limits, permissions needed, whether it's idempotent, or what happens on failure. For a mutation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that efficiently explain the tool's function. It's front-loaded with the core purpose and avoids unnecessary details. However, it could be slightly more structured by explicitly naming the tool or separating key points.
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 (a mutation operation with no annotations and no output schema), the description is incomplete. It doesn't cover important aspects like what the tool returns, error handling, or side effects. For a CDN prefetch tool that modifies cache state, more context is needed to ensure safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the 'urls' parameter thoroughly (e.g., max 60 items, full URLs with protocol). The description adds minimal value beyond the schema by mentioning 'resource URLs' and 'prefetch process,' but doesn't provide additional semantics like URL formatting rules or usage examples not in the schema. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'proactively retrieved by the CDN and stored on its cache nodes in advance' and 'submit the resource URLs, and the CDN automatically triggers the prefetch process.' It specifies the verb (prefetch/retrieve) and resource (URLs/CDN cache), but doesn't explicitly distinguish it from sibling tools like 'cdn_refresh' which might have overlapping functionality.
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 mentions 'newly added resources' but doesn't specify prerequisites, timing, or compare it to siblings like 'cdn_refresh' (which might refresh existing cache) or other CDN-related tools. Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool retrieves object contents but doesn't describe what 'contents' means (e.g., raw data, metadata), whether authentication is required, rate limits, error conditions, or the format of the return value. This leaves significant gaps for a tool that performs a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences that directly address the tool's function and parameter usage. It avoids unnecessary fluff, though it could be slightly more front-loaded by starting with the core purpose more explicitly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a cloud storage retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'contents' includes (e.g., file data, metadata), potential authentication needs, error handling, or return format, leaving the agent with incomplete context for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for both 'bucket' and 'key' parameters. The description adds minimal value beyond the schema by mentioning 'specify the full key name,' which is already implied by the schema. This 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get an object contents') and resource ('from Qiniu Cloud bucket'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'get_object_url' or 'list_objects' that might also retrieve object information, 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.
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 when to choose 'get_object' over 'get_object_url' (which might return a URL instead of contents) or 'list_objects' (which lists objects rather than retrieving contents), nor does it specify any prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that binding 'allows you to configure the domain for playing back streams' but lacks critical details such as required permissions, whether this operation is idempotent or reversible, potential side effects (e.g., impact on existing configurations), or error conditions. This is a significant gap for a mutation 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, consisting of two sentences that directly state the tool's purpose and benefit. There is no redundant information, and it efficiently communicates the core functionality without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a domain-binding operation for live streaming, the description is incomplete. No annotations are provided to cover behavioral aspects, and there is no output schema to explain return values. The description fails to address key contextual elements like authentication requirements, rate limits, or what happens after binding (e.g., propagation time, verification steps), making it inadequate for safe and effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters (bucket, domain, domain_type) with clear descriptions. The description adds no additional semantic context beyond what's in the schema, such as explaining the relationship between parameters or providing examples beyond the schema's domain example. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Bind') and the resources involved ('a playback domain to a LiveStreaming bucket'), specifying the purpose for live streaming configuration. It distinguishes from the sibling tool 'live_streaming_bind_push_domain' by focusing on playback rather than push domains, though this differentiation is implicit rather than explicit.
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 does not mention prerequisites (e.g., needing an existing bucket or domain), exclusions, or compare it to related tools like 'live_streaming_get_play_urls' or 'live_streaming_create_stream', leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the configuration outcome without disclosing behavioral traits like required permissions, whether binding is reversible, rate limits, or error conditions. It mentions RTMP/WHIP streams but doesn't explain operational implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence and adds clarifying context in the second. Both sentences earn their place by explaining the action and its purpose, with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on success/failure responses, side effects, or integration with other tools like 'live_streaming_get_push_urls'. The context of live streaming is mentioned, but operational completeness is low.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds no additional parameter semantics beyond what's in the schema, such as format constraints or examples for 'bucket' or 'domain_type' beyond the default. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Bind') and resources involved ('push domain to a LiveStreaming bucket'), with a specific purpose for live streaming configuration. It distinguishes from sibling 'live_streaming_bind_play_domain' by specifying 'push' domain, though not explicitly contrasting them.
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 like 'live_streaming_create_stream' or prerequisites. It mentions the outcome ('configure the domain for pushing RTMP/WHIP streams') but lacks explicit when/when-not instructions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool creates a bucket and provides the resulting URL format, but lacks critical details: it doesn't specify if this is a mutating operation (implied but not explicit), what permissions are required, whether the bucket name must be unique, error handling, or rate limits. For a creation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two sentences that directly state the tool's purpose and outcome. Every word earns its place: 'Create a new bucket' defines the action, 'in LiveStreaming' specifies the context, 'using S3-style API' adds technical detail, and the URL format clarifies the result. There is no redundancy or unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a creation tool with no annotations and no output schema, the description is incomplete. It lacks essential context: it doesn't explain what a 'bucket' is in this system, what happens after creation (e.g., default settings), potential side effects, or return values. The URL format hint is helpful but insufficient for an agent to fully understand the tool's behavior and implications.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'bucket' documented as 'LiveStreaming bucket name'. The description adds minimal value beyond the schema by mentioning the resulting URL format ('https://<bucket>.<endpoint_url>'), which implies the bucket name is used in the URL. However, it doesn't provide additional semantics like naming constraints or examples. With high schema coverage, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new bucket') and resource ('in LiveStreaming'), and specifies the API style ('using S3-style API'). It distinguishes from siblings like 'list_buckets' and 'live_streaming_list_buckets' by focusing on creation rather than listing. However, it doesn't explicitly differentiate from other bucket-related tools beyond the creation aspect.
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 prerequisites, such as needing permissions or existing infrastructure, or when not to use it (e.g., for updating or deleting buckets). With siblings like 'list_buckets' and 'live_streaming_list_buckets', there's no explicit comparison or context for choosing this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the creation action and resulting URL pattern but doesn't disclose permission requirements, whether the operation is idempotent, error conditions, rate limits, or what happens if the stream already exists. 'Create' implies mutation but lacks safety context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with zero waste. The first sentence states the core purpose, the second provides useful implementation detail about the resulting URL structure. However, it could be more front-loaded with critical behavioral information given the lack of annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation/mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what 'create' entails operationally, what permissions are needed, what the response contains, or error handling. The URL format hint is helpful but insufficient for safe agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters fully. The description adds marginal value by showing how parameters combine in the resulting URL ('https://<bucket>.<endpoint_url>/<stream>'), but doesn't provide additional semantics beyond what the schema descriptions ('LiveStreaming bucket name', 'LiveStreaming stream name') already convey.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new stream') and resource ('in LiveStreaming'), with specific technology context ('using S3-style API'). It distinguishes from siblings like 'live_streaming_list_streams' (list vs create) and 'live_streaming_create_bucket' (bucket vs stream), but doesn't explicitly differentiate from other creation tools.
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?
No guidance on when to use this tool versus alternatives. The description mentions the resulting URL format but doesn't specify prerequisites (e.g., bucket must exist), use cases, or when to choose this over other streaming tools like 'live_streaming_bind_play_domain'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool returns URLs for playback, implying a read-only operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, or whether the URLs are ephemeral. This is a significant gap for a tool with no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with two sentences that directly state the purpose and output. There's no unnecessary information, but it could be slightly improved by integrating usage context without adding bulk.
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 (3 required parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain the return format beyond URL types, lacks error handling details, and omits prerequisites like stream existence. For a tool with no structured output or annotations, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the baseline is 3. The description adds no additional meaning beyond the schema, such as explaining how parameters relate to each other or providing examples. It relies entirely on the schema for parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get playback URLs for a stream' specifies the verb ('Get') and resource ('playback URLs'), and it distinguishes the tool by mentioning the URL types returned (FLV, M3U8, WHEP). However, it doesn't explicitly differentiate from sibling tools like 'live_streaming_get_push_urls' or 'get_object_url', which slightly reduces clarity.
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 prerequisites, such as needing an existing stream, or compare it to similar tools like 'live_streaming_get_push_urls' or 'get_object_url', leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return values (total traffic, average bandwidth, peak bandwidth, optional raw data) but lacks critical details: it doesn't specify if this is a read-only operation, what permissions are required, whether there are rate limits, or how the data is formatted (e.g., units, timezone). For a query tool with no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first in a single sentence. The second sentence efficiently lists return values and the optional raw data feature. There's no wasted text, making it easy to scan, though it could be slightly more structured (e.g., bullet points for returns).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (querying statistics with 3 parameters) and no annotations or output schema, the description is partially complete. It covers the purpose and return values but lacks behavioral details (e.g., read-only status, error handling) and doesn't fully compensate for the missing output schema. It's adequate as a minimum viable description but has clear gaps in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents the parameters (begin, end, include_raw_data). The description adds minimal value beyond the schema: it implies time-range filtering and mentions the optional raw data parameter, but doesn't provide additional context like valid time ranges, timezone handling, or what 'raw data' entails. This meets the baseline of 3 when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Query live streaming traffic statistics for a time range.' It specifies the verb ('query'), resource ('live streaming traffic statistics'), and scope ('for a time range'). However, it doesn't explicitly differentiate from sibling tools like 'live_streaming_list_streams' or 'live_streaming_get_play_urls', which might also involve live streaming data but serve different purposes.
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 mentions an optional parameter for raw data but doesn't explain when to include it or how it differs from the default output. With many sibling tools (e.g., 'live_streaming_list_streams', 'live_streaming_get_play_urls'), there's no indication of when this query tool is preferred over others for accessing live streaming data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'upload' implies a write operation, it doesn't disclose important behavioral traits like authentication requirements, rate limits, file size limitations, network timeout behavior, or what happens on failure. The description is minimal and lacks operational context needed for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that states the core purpose without any fluff. It's front-loaded with the essential information and contains zero wasted words. This represents optimal conciseness for a basic tool description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a file upload tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after upload (success/failure responses, returned identifiers), doesn't mention file format restrictions or size limits, and provides no context about the Qiniu service. The agent would need to guess about important operational aspects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the input schema already documents all 4 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain parameter relationships, provide examples, or clarify edge cases. The baseline score of 3 reflects adequate but minimal value addition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('upload') and target resource ('a local file to Qiniu bucket'), making the purpose immediately understandable. It distinguishes from siblings like 'upload_text_data' by specifying 'local file' rather than text data. However, it doesn't explicitly differentiate from all sibling tools beyond this basic distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'upload_local_file' over 'upload_text_data' for different content types, or when to use it versus other storage operations. There's no context about prerequisites, limitations, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the upload action but doesn't mention authentication requirements, rate limits, error conditions, or what happens upon success/failure. For a write operation with zero annotation coverage, this leaves significant gaps in understanding tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with zero wasted words. It immediately communicates the core function without unnecessary elaboration, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a write operation with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what happens after upload, error handling, authentication needs, or how this differs from similar tools. The agent lacks critical context to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds no additional parameter information beyond what's already in the structured fields, meeting the baseline expectation but not providing extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Upload') and target resource ('text data to Qiniu bucket'), making the purpose immediately understandable. It distinguishes from sibling 'upload_local_file' by specifying text data rather than local files, though it doesn't explicitly contrast them.
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?
No guidance is provided on when to use this tool versus alternatives like 'upload_local_file' or other storage operations. The description lacks context about prerequisites, appropriate scenarios, or limitations that would help an agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool provides 'version info' but doesn't disclose behavioral traits like whether it's a read-only operation, if it requires authentication, rate limits, or what format the information returns. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one short sentence) and front-loaded with the core purpose. There's no wasted verbiage or unnecessary elaboration. However, it could be slightly more informative without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema) and the lack of annotations, the description is minimally adequate but incomplete. It identifies the tool's purpose but doesn't provide enough context about what 'version info' entails or how it differs from other server status tools that might exist in similar systems.
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 schema fully documents the lack of inputs. The description doesn't need to add parameter information, and the baseline for zero parameters is 4. No additional semantic value is required or provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states what the tool does ('version info') but is vague about the specific resource or scope. It mentions 'qiniu mcp server' but doesn't specify if this returns software version, API version, or server status. While it distinguishes from siblings by being the only version-related tool, the purpose lacks precision.
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?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, typical use cases, or contextual triggers. Given it's a simple version check tool among many CDN/object storage tools, some basic usage context would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information (implying read-only), but doesn't cover critical aspects like error handling (e.g., invalid URLs), performance (e.g., latency), authentication needs, or rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Retrieves basic image information') and specifies key details (format, size, color model). There is no wasted language or redundancy, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers what the tool does but lacks context on usage, behavioral traits, or output format. Without annotations or an output schema, the description should ideally explain the return structure (e.g., JSON with fields), but it doesn't, leaving room for improvement in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'object_url' well-documented in the schema (URL of the image, length constraints, examples of sources). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('basic image information'), specifying the exact data returned (format, size, color model). It distinguishes itself from siblings like 'get_object' (which likely retrieves the full image data) by focusing on metadata extraction rather than file retrieval. However, it doesn't explicitly contrast with all siblings, keeping it at a 4 rather than a 5.
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 prerequisites (e.g., needing a URL from 'get_object_url'), exclusions (e.g., not for video files), or comparisons to similar tools like 'get_object'. Without this context, an agent might misuse it or overlook better options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that it 'Returns the list of streams,' but doesn't specify format, pagination, error conditions, or authentication requirements. For a read operation with zero annotation coverage, this leaves significant gaps in understanding 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and followed by a brief note on the return value. Every word earns its place with no redundancy or fluff, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic action and return, but lacks details on behavior, usage context, or output format, leaving room for improvement in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents the single parameter 'bucket_id' with its description. The description adds no additional meaning beyond what's in the schema, such as examples or constraints, resulting in the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all streams in a specific live streaming bucket'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_buckets' or 'list_objects', which would require a 5.
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 like 'list_buckets' or 'list_objects', nor does it mention prerequisites or exclusions. It only states what the tool does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns URLs but doesn't describe any behavioral traits such as authentication requirements, rate limits, error conditions, or whether it's a read-only operation. For a tool with zero annotation coverage, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with two sentences that are front-loaded and efficient. The first sentence states the purpose, and the second adds useful detail about the return types. There's no wasted text, but 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 required parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and return types but lacks details on behavioral aspects, error handling, or integration with sibling tools. Without annotations or output schema, more context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters with descriptions. The description doesn't add any meaning beyond what the schema provides, such as explaining relationships between parameters or usage examples. Baseline 3 is appropriate when the schema handles parameter documentation effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get push URLs') and resource ('for a stream'), specifying what the tool does. It distinguishes from siblings like 'live_streaming_get_play_urls' by focusing on push URLs rather than play URLs. However, it doesn't explicitly differentiate from other push-related tools like 'live_streaming_bind_push_domain', which slightly reduces specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing push URLs for live streaming, but doesn't explicitly state when to use this tool versus alternatives like 'live_streaming_create_stream' for setup or 'live_streaming_bind_push_domain' for domain configuration. It mentions the return types (RTMP and WHIP URLs), which provides some context, but lacks clear exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'Returns information about all available live streaming buckets' which hints at read-only behavior, but doesn't specify what information is returned, whether there's pagination, rate limits, authentication requirements, or error conditions. For a tool with zero annotation coverage, this is insufficient behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two clear sentences that directly state the tool's function and return value. Every word earns its place with no redundancy or unnecessary elaboration. It's appropriately sized for a simple listing tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does and what it returns, but lacks details about the return format, error handling, or operational constraints. For a listing tool without annotations, more context about the response structure would be helpful.
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 is 4. The description doesn't need to explain parameters, and it correctly doesn't mention any. No additional parameter semantics are needed or provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List all live streaming spaces/buckets' with the verb 'List' and resource 'live streaming spaces/buckets'. It distinguishes from generic 'list_buckets' by specifying 'live streaming' scope, though it doesn't explicitly differentiate from 'live_streaming_list_streams' which lists streams rather than buckets.
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?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention when to choose this over 'list_buckets' (for general storage) or 'live_streaming_list_streams' (for streams within buckets). The description only states what it does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the core behavior (expiring cache, triggering refetch) but doesn't disclose important traits like whether this is a destructive/mutative operation (implied by 'marks as expired'), authentication requirements, rate limits, error handling, or what happens if URLs are invalid. For a mutation tool with zero 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero waste: the first states the action and immediate effect, the second explains the downstream consequence. It's front-loaded with the core purpose and efficiently structured without redundancy.
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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, permissions, or response format, nor does it address the tool's role relative to siblings. For a tool that modifies CDN state, more context is needed to use it safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('urls' and 'dirs') with details on format, patterns, and limits. The description adds no additional parameter semantics beyond what the schema provides, but since the schema is comprehensive, 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('marks resources cached on CDN nodes as expired') and explains the consequence ('CDN nodes will fetch the latest version from the origin server'). It distinguishes this tool from siblings like 'cdn_prefetch_urls' (which likely preloads content) and various image/upload tools by focusing on cache invalidation rather than content retrieval or manipulation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need to force CDN cache updates for specific resources, but it doesn't explicitly state when to use this tool versus alternatives like 'cdn_prefetch_urls' or when not to use it (e.g., for bulk operations beyond limits). The context is clear but lacks explicit guidance on alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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. It adds important context about domain binding requirements and HTTPS limitations with test domains, which are not covered in the input schema. However, it doesn't describe critical behaviors like authentication needs (implied by 'expires' parameter for private buckets), rate limits, error conditions, or what the output looks like (URL format). The description provides some value but 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise with two sentences. The first sentence states the core purpose, and the second adds important constraints. However, the second sentence is somewhat complex and could be structured more clearly. No wasted words, but the information density could be improved.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters, 100% schema coverage, but no annotations and no output schema, the description provides some useful context about domain requirements and HTTPS limitations. However, it doesn't explain the return value (URL format), error conditions, or authentication implications fully. Given the complexity of URL generation with SSL and expiration considerations, the description should do more to compensate for the lack of output schema and annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions domain binding and HTTPS considerations generally but doesn't link these to specific parameters like 'disable_ssl' or 'bucket'. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get the file download URL' specifies the verb (get) and resource (file download URL). It distinguishes from siblings like 'get_object' (which likely retrieves the object itself) by focusing on URL generation. However, it doesn't explicitly differentiate from CDN-related URL tools like 'cdn_prefetch_urls' or 'live_streaming_get_play_urls'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context by mentioning domain binding requirements and HTTPS limitations with test domains, which implies when this tool is appropriate. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_object' (for direct file access) or CDN tools for prefetching/refreshing URLs. No clear exclusions or prerequisites are defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: pagination behavior ('list a part each time'), continuation logic ('start_after to continue listing'), and completion detection ('when the number of listed objects is less than max_keys, it means that all files are listed'). However, it doesn't cover error conditions, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized at three sentences, front-loading the core purpose. Each sentence adds value: the first states the action, the second explains pagination and completion logic, and the third clarifies 'start_after'. There's no redundant information, though it could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides adequate context for a read-only listing tool with pagination. It covers the main behavioral aspects but lacks details on return format, error handling, or authentication. For a tool with 4 parameters and complex pagination logic, it's minimally complete but leaves gaps an agent might need.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema—it mentions 'start_after' for continuation and implies 'max_keys' for pagination, but doesn't provide additional semantic context or usage examples that aren't already in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('objects in Qiniu Cloud'), making the purpose unambiguous. It distinguishes itself from sibling tools like 'list_buckets' by specifying it lists objects within a bucket, but doesn't explicitly contrast with other object-related tools like 'get_object'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for paginated listing with continuation via 'start_after', suggesting when to use it for large result sets. However, it doesn't provide explicit guidance on when to choose this tool over alternatives like 'get_object' or 'list_buckets', 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it specifies that the tool returns an 'object_url' for HTTP GET requests, details supported image formats, size constraints (width/height ≤ 30,000 pixels, total ≤ 150 million pixels), and rules for radius values (non-negative, pixels or percentages). It also explains the default behavior when only one radius is set. This covers many operational aspects, though it could mention error handling or performance implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose but becomes verbose with detailed specifications (e.g., supported formats, size limits, radius rules). While informative, some sentences could be more streamlined, and the structure mixes operational details with prerequisites, reducing overall conciseness. It's adequately sized but not optimally efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (image processing with constraints) and no annotations or output schema, the description compensates well by covering prerequisites (Qiniu Cloud Bucket), input constraints (formats, sizes), parameter behavior, and output details (object_url usage). It provides a solid foundation for an agent to use the tool correctly, though it could benefit from mentioning error cases or linking to sibling tools for context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear details for 'object_url,' 'radius_x,' and 'radius_y.' The description adds some value by explaining the relationship between radius parameters (if only one is set, the other gets the same value) and elaborating on radius formats (pixels vs. percentages with examples). However, it doesn't introduce new parameter meanings beyond what the schema already covers, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'processes images based on width, height, and corner radius, returning information about the processed image,' which specifies the verb (processes), resource (images), and operation (rounding corners). However, it doesn't explicitly differentiate from sibling tools like 'image_scale_by_percent' or 'image_scale_by_size,' which also process images but for different transformations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating prerequisites such as 'The image must be stored in a Qiniu Cloud Bucket' and listing supported formats and size limits. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., other image processing siblings) or any exclusions, leaving the context somewhat inferred rather than clearly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and adds valuable behavioral context: it explains the return format (object_url for HTTP GET), storage requirements (Qiniu Cloud Bucket), format support (9 specific formats), and size constraints (width/height ≤30,000px, total ≤150M pixels). It doesn't mention error conditions, rate limits, or authentication needs, but provides substantial 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with the core purpose, explains the return value, then lists requirements and constraints. Every sentence adds value, though it could be slightly more concise by combining some constraint statements.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter tool with no annotations and no output schema, the description provides good context: purpose, return format, storage requirements, format support, and size constraints. It doesn't explain error cases or provide examples, but covers the essential operational context given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions the object_url can come from GetObjectURL or other Fop tools, but this is more usage guidance than parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Image scaling tool that resizes images based on a percentage and returns information about the scaled image.' It specifies the verb (resizes/scales), resource (images), and operation (percentage-based scaling). However, it doesn't explicitly differentiate from sibling 'image_scale_by_size' which likely scales by dimensions rather than percentage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some contextual guidance: 'The image must be stored in a Qiniu Cloud Bucket' and lists supported formats and size constraints. However, it doesn't explicitly state when to use this tool versus the sibling 'image_scale_by_size' tool, nor does it mention prerequisites like authentication or rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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. It effectively describes key behaviors: the tool returns an object_url for HTTP GET access, specifies supported image formats (psd, jpeg, etc.), and outlines constraints (width/height ≤30,000 pixels, total pixels ≤150 million). It also notes proportional scaling when width or height is specified. However, it lacks details on error handling, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized, with key information front-loaded (purpose and return value). Each sentence adds value: the first states the purpose, the second explains the object_url usage, the third specifies the bucket requirement, and the fourth lists format and size constraints. There is no redundant information, though it could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, return value usage, prerequisites (Qiniu Cloud Bucket), supported formats, and size constraints. However, it lacks details on output structure (beyond object_url) and error conditions, which would be helpful for an agent invoking the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal parameter semantics beyond the schema, only implying that width and height are used for proportional scaling. It does not clarify if both can be used simultaneously or their interaction. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Image scaling tool that resizes images based on a specified width or height and returns information about the scaled image.' It specifies the verb (resizes/scales), resource (images), and distinguishes from sibling tools like image_scale_by_percent (which scales by percentage rather than dimensions) and image_info (which retrieves metadata without scaling).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some contextual guidance: 'The image must be stored in a Qiniu Cloud Bucket' and lists supported formats and size constraints. However, it does not explicitly state when to use this tool versus alternatives like image_scale_by_percent, nor does it mention prerequisites (e.g., needing an object_url from GetObjectURL). Usage is implied but not clearly differentiated from siblings.
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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