normahub_generate_video

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

With no annotations, the description carries the full burden, and it does disclose one important behavioral trait: it 'automatically polls until video render completes,' implying a long-running, blocking call. It omits cost implications, expected wait times/timeouts, failure behavior, and whether copyrighted or safety filters apply, all material for a paid video-generation call.

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?

Two tight sentences that front-load the capability before the operational detail. Nothing extraneous, though it is thin for a tool of this complexity.

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 generation tool with no output schema, the description should explain what a caller gets back (video URL, asset id, job id) and what the polling window can cost in time. It covers the operation but leaves the return contract and practical limits unstated.

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 100%, so both the prompt and model parameters (including the model list) are already fully documented in the schema. The description adds no syntax, defaulting, or prompt-engineering guidance beyond that.

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 names a specific verb and resource ('Generate AI videos') and identifies the underlying backends (SeeDance 2.5/2.0, Grok Imagine Video) and the NormaHub API. It doesn't explicitly contrast with the sibling normahub_image_to_video, but the text-to-video purpose is clear.

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?

There is no guidance on when to pick this over normahub_image_to_video or normahub_prompt_model, and no stated preconditions. The only implicit cue is that this tool is for text-prompt-driven generation, which the schema already conveys.

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