opentweet_generate_video

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

Annotations include openWorldHint=true, idempotentHint=false, destructiveHint=false. The description adds transparency by detailing the async polling process, maximum wait time, and the requirement for an API key, which go beyond the annotations.

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 two concise sentences. The first sentence states the purpose; the second covers behavior, output, and prerequisites. No wasted words, and critical information is front-loaded.

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 4 parameters, no output schema, and annotations, the description covers purpose, async behavior, return value, and key requirement. It is fairly complete but could mention failure scenarios or timeout handling.

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% with descriptions for all parameters. The description mostly restates schema information (e.g., duration range, resolution defaults) without adding significant new meaning beyond the schema.

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: generating an AI video from a text prompt using Grok Imagine. It specifies the verb 'generate' and the resource 'video', distinguishing it from sibling tools like opentweet_generate_image.

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 explains the async behavior, polling mechanism, and required API key. It tells when to use (for video generation) but does not explicitly mention when not to use or provide alternative tools, though the async note guides appropriate usage.

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