generate_img_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 effectively describes key behavioral traits: it's a generative tool that may incur costs, has model-specific defaults and constraints (e.g., duration and resolution options), and returns a task_id and video_url. It also notes that BGM is only supported for 4-second videos. While comprehensive, it could benefit from mentioning potential rate limits or error handling, keeping it from a perfect score.

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 well-structured with clear sections (purpose, cost warning, args, returns) and uses bullet points for readability. It's appropriately sized for an 8-parameter tool, with each sentence adding value. However, some redundancy exists (e.g., repeating model names in multiple sections), and the opening sentence could be more front-loaded with key details, slightly reducing efficiency.

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 8 parameters, no annotations, and no output schema, the description is highly complete. It covers purpose, usage warnings, detailed parameter semantics, and return values. The only minor gap is the lack of explicit differentiation from sibling tools, but given the richness of other details, this is a strong effort that nearly meets all contextual needs.

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 a schema description coverage of 0%, the description compensates fully by providing detailed semantics for all 8 parameters. It explains each parameter's purpose, default values, allowed values (e.g., model options, resolution options), and constraints (e.g., prompt length limit, BGM support conditions). This goes well beyond the basic schema, making it easy for an agent to understand how to use each parameter correctly.

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.' It specifies the verb ('generate'), resource ('video'), and input types ('pic and prompt'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'generate_text_to_video' or 'generate_template_to_video', 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.

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

The description provides clear usage guidance with a 'COST WARNING' that advises using the tool only when explicitly requested by the user, which helps prevent unnecessary API calls. It also mentions model-specific defaults and constraints (e.g., BGM only supported for 4-second videos), offering practical context. However, it doesn't explicitly state when to use this tool versus its siblings (e.g., 'generate_text_to_video'), which limits the score.

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