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Generate video

generate_video

Generate videos from text prompts with Grok AI. Submit a prompt to get a requestId, poll for the render, and download the final clip.

Instructions

Submit a Grok video generation from a text prompt. Returns a requestId to poll with get_generation and download with get_video. Generation takes 1-5 minutes. ~$0.005/sec.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText description of the video to generate
durationNoDuration in seconds (default 8)
resolutionNoResolution (grok-imagine-video-1.5 supports 1080p)
aspectRatioNoAspect ratio (default 16:9)
Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It discloses that generation is asynchronous (returns a requestId), takes 1-5 minutes, and costs ~$0.005/sec. These are important behavioral traits beyond the schema. It does not cover failure handling or permissions, but the key operational facts are present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the primary action, and every sentence adds value: the operation, the follow-up flow, and operational constraints (time and cost). There is no wasted wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema and annotations, the description covers the core workflow (submit, poll, download), timing, and cost. It could explicitly mention the synchronous alternative generate_and_wait, but overall it provides sufficient context for an agent to invoke the tool correctly and understand what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with descriptions for all parameters, so the baseline is 3. The description adds no additional parameter-level detail beyond what the schema provides, but none is needed since the schema already explains prompt, duration, resolution, and aspect ratio.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Submit' and identifies the resource 'Grok video generation', making the tool's function unmistakable. It distinguishes itself from siblings by stating it returns a requestId to poll with get_generation and download with get_video.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an explicit workflow: submit the prompt, then poll and download using the specified sibling tools. This clearly implies when to use this tool (to initiate generation). It does not mention generate_and_wait as a synchronous alternative, but the core usage context is well established.

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

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