query_generate_task

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It only says 'query results' and does not mention whether tasks can be in progress, whether the tool polls, what the response contains, or whether this is read-only in any meaningful sense.

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 one short sentence with no filler and is front-loaded. It is concise, though a little additional context could be added without hurting clarity.

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

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

With no output schema and no annotations, the description should at minimum clarify what kind of result is returned, whether the call blocks or returns a status, and how it connects to generate_image. Saying only '任务结果' leaves these essential details unspecified.

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 already fully documents the single key parameter as '发起作画返回的任务key'. The description adds no additional meaning about key format, where to get it, or how to use it, so it sits at the baseline for full schema coverage.

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

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

The description states a specific operation: '查询作画任务结果' (query the result of an image-generation task). The verb+resource combination clearly distinguishes it from siblings generate_image and query_model_infos.

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 text explains when to call this tool versus generate_image or query_model_infos. The agent must infer from sibling names that this is the follow-up after image generation; there are no explicit alternatives, conditions, or exclusions.

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