generate_reference2video_to_video

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 does well by including the cost warning about API calls to Vidu, which is crucial behavioral context not in the schema. It also describes return values ('task_id and video_url'), though output format details are minimal. It doesn't cover error handling, rate limits, or authentication needs, leaving some gaps.

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 appropriately front-loaded with the core purpose and cost warning. However, it's lengthy due to detailed parameter explanations, which are necessary given the poor schema coverage. Some redundancy exists (e.g., repeating 'Defaults to' for multiple parameters), and the structure could be tighter, but overall it's reasonably organized for a complex tool.

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?

For a complex tool with 9 parameters, 0% schema coverage, no annotations, and no output schema, the description does a good job of providing necessary context. It covers purpose, cost behavior, parameter semantics, and return values. It lacks details on error cases, rate limits, and full output structure, but given the constraints, it's mostly complete and actionable.

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?

Given 0% schema description coverage, the description compensates fully by providing detailed semantic information for all 9 parameters. It explains each parameter's purpose, constraints (e.g., '1 to 3 images', 'maximum length of 1500 characters'), defaults, accepted values, and interdependencies (e.g., model-specific duration and resolution options). This adds significant value beyond the bare 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 the tool's purpose: 'Generate a video from a pic and prompt.' This specifies the verb ('generate') and resource ('video'), though it uses 'pic' instead of the more accurate 'images' from the schema. It distinguishes from siblings like 'generate_text_to_video' by mentioning image input, but doesn't explicitly contrast with all siblings (e.g., 'generate_template_to_video').

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 provides clear usage guidance with the 'COST WARNING' section, advising to 'Only use when explicitly requested by the user.' This establishes a specific context for when to invoke the tool. However, it doesn't explicitly mention when to choose this tool over sibling tools (e.g., vs. 'generate_img_to_video'), which would be needed for a perfect score.

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