grok_text_to_video

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

With no annotations provided, the description carries the full burden. It discloses the async nature by stating 'Returns: Task ID and generated video information including URLs and state,' which implies polling. It also mentions model-specific durations, cost implications of resolution, and callback behavior. Minor gap: it doesn't explicitly state that generation is asynchronous or mention failure/error handling, but the return-type disclosure is strong.

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 well-structured: purpose sentence, context, explicit use cases, sibling-tool reference, model compatibility note, and a concise returns section. Every sentence earns its place, and it is front-loaded with the primary action. No redundancy or filler.

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 six parameters with complex model constraints, the description covers all necessary operational context: supported models, duration limits, resolution cost implications, aspect ratio usage, callback behavior, and return type. It is complete for a task-creation tool with rich schema and no need to explain return values beyond the stated task ID and URLs.

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%, so the baseline is 3. The description adds critical value beyond the schema by clarifying which models support text-to-video and explicitly warning against using 'grok-imagine-video-1.5:official' for this tool. This prevents a common mistake and adds semantic meaning not present in the schema enum alone.

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 opens with a specific verb+resource statement: 'Generate AI video from a text prompt using Grok Imagine.' It clearly distinguishes the tool from its sibling grok_image_to_video by explicitly noting that image-to-video should use that sibling tool. The 'Use this when' bullets further narrow the purpose to text-only generation with creative freedom.

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?

Explicit 'Use this when' bullets provide clear usage context, and the description directly names the alternative tool for reference-image inputs. It also lists the exact models that support text-to-video, warning against using an incompatible model. This gives unambiguous when-to-use and when-not-to-use guidance.

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