luma_generate_video_from_image

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

No annotations exist, so the description must disclose behavioral traits. It mentions generating 'smooth motion' and returns 'Task ID and generated video information.' However, it does not clarify if the operation is asynchronous (suggested by callback_url parameter), potential rate limits, or other side effects. For a generation tool, more transparency about the async nature would be beneficial.

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 about 100 words, well-structured with bullet points for use cases. It is concise and front-loaded with the main action. However, it could be slightly more concise by avoiding redundancy in the use case list.

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 (8 parameters, generation tool, likely async), the description covers the core functionality but lacks details on the async workflow (returning a task ID and then later polling) and explanation of parameters like callback_url and timeout. The output schema likely covers return values, but the description should mention the async behavior for completeness.

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 coverage is 100%, so baseline is 3. The description adds meaning by explaining the role of start_image_url and end_image_url and the constraint on providing at least one. However, it does not elaborate on parameters like timeout, callback_url, or loop beyond what the schema already defines. It adds marginal value.

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 AI video using reference images as start and/or end frames.' It specifies the action (generate), resource (video from images), and scope (using start/end frames). This distinguishes it from sibling tools like luma_generate_video (no images) and luma_extend_video (extend existing 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 explicit use cases: when you have a specific image to animate, want a transition between two images, or need control over visual content. It also states the constraint 'At least one of start_image_url or end_image_url must be provided.' While it doesn't explicitly say when not to use it, the use cases are clear and help the agent choose between this and alternatives.

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