Skip to main content
Glama

Generate video and wait

generate_and_wait

Generate a video from a text prompt, wait for rendering to finish, and get the local file path—all in one call.

Instructions

Submit a Grok video generation, poll until complete (up to timeoutSeconds), and return the downloaded file path. The one-call convenience for agents.

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)
timeoutSecondsNoMax wait in seconds (default 900)
Behavior3/5

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

With no annotations supplied, the description carries the burden of behavioral disclosure. It reveals that the tool polls and downloads a file, but it does not disclose what happens on timeout or generation failure, whether files are temporary or persistent, or if any cleanup is needed. This is partial transparency, not a contradiction.

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 two sentences: a terse operational summary and a positioning sentence. It front-loads the core actions (submit, poll, return path) and avoids redundant detail. Every sentence earns its place.

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?

The tool has no output schema, so mentioning 'return the downloaded file path' is essential and done. Given the composite nature (generate + poll + download), the description covers the main workflow but omits failure behavior, timeout consequences, and any prerequisites. Still, for an agent, the essential contract is clear enough to invoke correctly in most cases.

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 schema already describes all parameters with 100% coverage. The description only references timeoutSeconds ('up to timeoutSeconds') without adding new meaning beyond what the schema states. It does not clarify parameter interactions or defaults beyond the schema. Baseline 3 is appropriate.

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 clearly states a specific verb-resource-action: 'Submit a Grok video generation, poll until complete, and return the downloaded file path.' This distinguishes it from siblings like generate_video (submit only) or get_generation (poll only), especially with the 'one-call convenience' framing.

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?

It says 'The one-call convenience for agents,' which implies using this tool instead of manually chaining generate_video and polling. It also mentions the timeoutSeconds bound. However, it does not explicitly name sibling tools or state when NOT to use this tool (e.g., when you don't want to wait).

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pongsakornp/grok-video-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server