llm_generate_video

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions 'external /v1 endpoint' but does not disclose authentication requirements (api_key), potential costs, output format, or whether the operation is synchronous. The description implies a write operation but lacks details on side effects or response handling.

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 sentence that front-loads the core action. The list of provider examples adds some value but is somewhat verbose. Overall, it is concise and to the point.

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?

With 6 parameters and no output schema, the description is insufficient. It does not explain the expected return value, error handling, or prerequisites like providing an API key. The agent would need to infer usage from parameter names and external knowledge, which is not ideal for a complex tool.

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?

The schema description coverage is 100%, so the baseline is 3. The description adds context about provider examples (SiliconFlow, Together, MiniMax) but does not clarify parameter relationships or usage beyond what the schema provides. It does not compensate for any missing semantic details, but the schema is adequate.

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 action ('Generate a video') and the resource ('video'), and mentions the external /v1 endpoint, which distinguishes it from sibling tools like llm_generate_image. However, it does not explicitly contrast it with alternatives, so differentiation is somewhat implied rather than stated.

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 use this tool versus other generation tools like llm_generate_image or llm_query. The description does not mention specific scenarios, prerequisites, or exclusions, leaving the agent to infer usage from the tool name and context.

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