generate_video

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

With no annotations, the description effectively conveys key behavioral traits: async execution (returns requestId, poll with check_job_status), pricing per second, duration constraints, and dependency on payment. It does not cover error handling or full output format, but adds substantial value beyond the schema.

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 a single, dense paragraph that front-loads the core function. It covers purpose, features, async, pricing, and dependencies in about 5 sentences with no redundancy. Could benefit from bullet points for readability, but remains concise.

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 (6 params, async, no output schema), the description covers input constraints, pricing, and async polling. However, it does not describe the output format or error codes, leaving an incomplete picture. The polling hint partially mitigates, but a full output description is needed.

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?

Input schema has 100% description coverage, so baseline is 3. The description enhances parameter semantics by explaining pricing implications of duration and mode, and noting that modelId is optional with a default. It also clarifies the payment flow via create_payment.

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 'Generate a video from a text prompt', specifies the model (Kling v3), and mentions key features like quality modes, audio, and async nature. It distinguishes from sibling tools like generate_image or animate_image by focusing on video generation from text.

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 context: when to use (for generating videos from text), payment prerequisites (requires create_payment), and polling (check_job_status). However, it lacks explicit comparisons to alternatives or exclusions, leaving some ambiguity against similar tools like animate_image.

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