生成视频

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

No annotations are provided, so the description carries full burden. It discloses that the task is time-consuming, the default wait is 60s, short tasks return a URL, and long tasks return a task_id. This is good behavioral context, though it could further detail error handling or failure modes.

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 two sentences, front-loaded with the main action, then efficient detail. Every sentence earns its place with no wasted words.

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

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

Given the complexity of a long-running generation task and no output schema, the description covers the essential workflow: prerequisite (describe_model), default wait, and fallback to get_task. It could mention error handling or output format more explicitly, but overall it is complete enough for an agent.

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

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

Schema description coverage is 100%, so parameters are fully documented there. The description adds workflow context (use describe_model for params, wait/retry behavior) but does not provide additional semantic details beyond the schema. Baseline 3 is appropriate.

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

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

The description clearly states '提交视频生成任务' (submit a video generation task), a specific verb+resource. While it does not explicitly differentiate from sibling tools like generate_audio or generate_image, the tool name and title already do that. The description adds the long-running nature, enhancing clarity.

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 advises using describe_model first to confirm parameters and mentions fallback to get_task on timeout. This provides sequential context but lacks explicit when-to-use versus alternatives or when not to use. Guidance is implied rather than explicit.

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