generate_video

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

Beyond the annotations it discloses the credit cost, the mandatory user-confirmation gate, provider-specific constraints (Grok 1-15s and 480p-1080p, reference-to-video capped at 720p), and that the call is asynchronous and must be polled via list_jobs for the final video_url. That is a lot of behavior an agent could not infer from readOnlyHint=false / openWorldHint=true alone.

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?

Three tight sentences: purpose, the credit/confirmation warning in caps, then provider constraints and the polling instruction. Front-loaded with the highest-risk information (it costs money) and no filler.

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 14-parameter, non-idempotent, open-world mutation with no output schema, it covers the decision-critical pieces: cost, confirmation, provider limits, and how to retrieve results. Gaps remain around the model tier enum and the image/end-image/source-video input modes, which an agent would have to guess from the schema alone.

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 only 21% across 14 parameters, so the description carries a heavy burden. It adds meaning for provider, duration, resolution, audio, and reference-image limits, but says nothing about model (lite/fast/standard), workspace_id, negative_prompt, image_url, end_image_url, or source_video_url, leaving roughly half the surface undocumented anywhere.

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?

"Queue an AI video generation job with Google Veo 3.1 or xAI Grok Imagine Video 1.5" names a specific verb, resource, and the two backing models, which separates it cleanly from generate_image and get_video_options in the sibling list.

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?

It gives an explicit precondition (confirm provider, prompt, duration, resolution, aspect ratio, audio, and credit cost with the user before calling) and names list_jobs with type=video as the follow-up step. It does not contrast itself with siblings like run_video_function or get_video_options, so routing between video tools is left partly to inference.

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