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

No annotations are provided, and the description only states the action 'create' plus a vague return message. It does not disclose side effects, idempotency, error handling, permissions, or any behavioral traits beyond the tool name itself.

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

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

The description is extremely concise with no redundant prose, using a clear Args/Returns structure. It is front-loaded with the purpose statement, though the brevity approaches under-specification.

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

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

With no output schema and no annotations, the description should clarify return values and edge cases. It only says 'str: 创建结果信息' (creation result message), lacking details on duplicate queue behavior, permissions, or failure modes, making it incomplete even for a simple tool.

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

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

The schema description coverage is 0%. The description's arg documentation 'queue_name (str): 队列名称' merely translates the parameter name and type, adding no meaning beyond the schema's 'Queue Name' title. It does not explain constraints, formats, or examples.

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

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

The description clearly states '创建一个 MNS 队列' (create an MNS queue), using a specific verb and resource. This distinguishes it from sibling tools like delete_queue, send_message, and list_queues, which perform different actions.

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, conditions, or any reference to sibling tools, leaving the agent to infer usage from context.

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

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

With no annotations provided, the description must disclose behavioral traits. It only states that a queue is deleted and a result string is returned, without mentioning that deletion is irreversible, whether messages in the queue are permanently removed, or any error conditions such as a nonexistent queue.

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

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

The description is extremely concise, consisting of a single sentence followed by structured Args/Returns sections. Every element is directly relevant, with no unnecessary fluff.

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

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

Given that this is a destructive operation with no annotations or output schema, the description lacks essential context about side effects, error handling, and prerequisites. It is too sparse to fully guide an agent in invoking the tool safely.

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

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

The description mentions queue_name but only restates it as '队列名称' (queue name), which duplicates the schema's title. It adds no additional semantics, constraints, or examples, offering little value beyond the input schema.

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

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

The description clearly states '删除 MNS 队列' (Delete MNS queue), using a specific verb and resource. This distinguishes it from sibling tools like create_mns_queue and list_queues.

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

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

No guidance is provided about when to use this tool versus creating, sending, or receiving messages. The description lacks any context about prerequisites or scenarios where deletion is appropriate.

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

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

With no annotations provided, the description discloses the return value format ('QueueName: <name>, QueueURL: <url>') and the conditional listing behavior. It implies a read-only operation but does not explicitly state side-effect-free or error behavior.

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

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

The description is compact and well-structured with summary, Args, and Returns sections. Each sentence provides essential information without redundancy.

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

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

Given the simple one-parameter interface and no output schema, the description adequately explains the parameter and the exact string format of returned list items. However, it omits potential pagination, ordering, or error conditions, which could be relevant for a production tool.

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

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

The input schema provides only a default value with no description (0% coverage). The description compensates by fully explaining the prefix parameter's meaning ('队列名称的前缀') and its default behavior, which is critical for correct usage.

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

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

The description explicitly states it retrieves all queues matching a prefix, or all queues if no prefix is given. This uses a specific verb ('获取'/'list') and resource ('queues'), and clearly distinguishes itself from the mutating sibling tools (create/delete/send/receive).

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

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

It provides clear context that the tool lists queues with an optional prefix filter, and explains the default behavior (no prefix = all queues). However, it does not explicitly mention when not to use it or refer to alternative sibling tools.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'delete' but does not explain that messages are permanently removed or emphasize the destructive nature beyond the tool's name. Missing side effects such as the impact on queue content or potential data loss.

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

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

The description is concise and front-loaded, starting with the main purpose then listing Args and Returns in a clean format. Every sentence adds value with no filler or repetition.

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

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

The description covers purpose, parameters, and return type, which is adequate for a simple two-parameter tool. However, it omits usage context (when to use versus siblings) and does not warn about the destructive deletion behavior, which is significant given no annotations or output schema to clarify.

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

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

Schema description coverage is 0%, so the description must compensate. It explains wait_seconds as 'long polling wait time in seconds' and queue_name as 'queue name', adding meaning beyond the schema's basic property titles. This is helpful, though it does not mention the default value or allowed ranges.

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

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

The description '接收并删除队列中的消息' clearly states it receives and deletes messages from a queue. This specific verb+resource combination distinguishes it from sibling tools like send_message, delete_queue, list_queues, and create_mns_queue.

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

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

The description implies usage as the only tool that consumes messages from a queue, but it does not explicitly state when to use it versus alternatives or provide any exclusion criteria. No guidance on prerequisites or when not to use it.

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

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

The description only states the action and return type. It does not disclose whether the queue must exist, what happens on failure, whether the operation is idempotent, or any side effects. Since no annotations are provided, the description carries the full burden and falls short.

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

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

The description is very concise and well-structured with an Args/Returns section. It is front-loaded with the primary purpose. However, it omits important usage context that would enhance completeness, so it's not a perfect 5.

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

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

The tool is simple, but the description lacks critical context such as requiring the queue to exist (created via create_mns_queue), what the returned result string contains, and error handling. This leaves the agent under-informed for invoking the tool successfully.

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

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

The description includes Chinese explanations for both parameters ('Queue name' and 'Message content'), but these essentially restate the parameter names. With 0% schema description coverage, the description provides minimal additional meaning but doesn't clarify formats, constraints, or edge cases.

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

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

The description clearly states 'Send a message to the specified queue' (发送消息到指定队列). This is a specific verb+resource combination that distinguishes it from sibling tools like create_mns_queue, receive_and_delete_messages, and list_queues.

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

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

The usage is implied by the name and purpose, but there is no explicit guidance on when to use it vs alternatives, nor any mention of prerequisites such as the queue needing to exist before sending. No exclusions or alternative references are provided.

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