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

Annotations indicate readOnlyHint=false, openWorldHint=true, destructiveHint=false. The description adds the resolution rejection behavior and the 1-3 second duration constraint, which are useful. It also discloses the cost (125 MESH/call) and the xAI non-affiliation disclaimer. However, it doesn't describe what happens on failure, whether the video is returned as a file or URL, or any rate limits. The description doesn't contradict annotations, but it doesn't add deep behavioral context beyond the constraints.

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 concise and front-loaded with the core function. The first sentence states the action, resource, and constraints. The additional notes about xAI and cost are brief and placed at the end. The parenthetical '(125 MESH/call, a tool · media)' is a bit cluttered but not overly verbose. It earns a 4 because it's efficient, though the parenthetical could be cleaner.

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 simple video generation tool with one parameter and no output schema, the description covers the essential constraints (duration, resolution, cost). However, it lacks information about the output format (e.g., file type, URL), how to handle failures, and whether there are content restrictions. The schema's generic example is not tailored to this tool, so the description carries the burden of explaining the input, which it does only partially ('text prompt' is vague). Overall, it's adequate but has gaps.

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 the schema already documents the single 'input' parameter. The description adds that the input is a text prompt, which is helpful but somewhat redundant with the tool's purpose. The schema's example mentions capability-specific payloads (agent-brain, agent-memory), which is confusing for a video generation tool, but the description clarifies the intended use. The description doesn't provide detailed syntax for the input object beyond 'text prompt', so it doesn't fully compensate for the schema's generic example.

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 function: generate a 1-3 second 480p video from a text prompt. It specifies the resource (video generation), the action (generate), and a key constraint (480p resolution). It doesn't explicitly differentiate from sibling tools like grok-image or grok-image-hq, but the video-specific wording and resolution constraint make the purpose reasonably distinct.

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 implies usage context: when a user wants a short 480p video from text. It explicitly states that any resolution other than 480p is rejected, which is a clear constraint. However, it doesn't provide explicit when-to-use vs alternatives guidance, such as 'use grok-image for still images' or 'use grok-video-1080p for higher resolution.' The sibling list includes grok-image and grok-image-hq, but the description doesn't mention them.

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