image_to_video

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

The description discloses the async nature (polls until completion, may take minutes) and return values (dict with video_id, etc.), which are beyond the schema. With no annotations, this is valuable context, though it lacks details on failure modes or quotas.

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 well-structured: a one-sentence summary, one paragraph on async behavior, then a bulleted Args list. Every sentence adds value, and the most important information is front-loaded.

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 async tool with many parameters, the description covers input, process, and output comprehensibly. It explains the polling mechanism and return dict, making the tool's behavior fully understandable.

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?

All 11 parameters are explained in the Args list, adding meaning beyond the bare-bones schema (0% coverage). For example, num_frames includes the '8n+1 rule' and common values with approximate durations, which is highly informative.

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 it animates a static image into a video, specifying input types (image URL/base64, text prompt). It is specific and distinct from siblings like text_to_video (no image input) or image_to_image (no video output), but does not explicitly differentiate usage cases.

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?

Usage is implied through required inputs (image and prompt), suggesting when the tool is appropriate. However, no explicit guidance on when to use alternatives or when not to use this tool is provided, leaving the agent to infer usage context.

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