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routara_generate_video

Submit an asynchronous video generation job from text or image prompts. Poll the returned task ID until completion.

Instructions

Submit an asynchronous video-generation job through Routara.

Supports text-to-video and image-to-video. Save the returned id or task_id and poll it with routara_get_video_status until completed or failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fpsNo
modelYesVideo model slug from routara_list_models
promptYesScene and motion description
durationNo
image_urlNoStarting frame for image-to-video
resolutionNoModel-specific resolution such as 720p or 1080p
aspect_ratioNoAspect ratio such as 16:9 or 9:16
negative_promptNo
Behavior3/5

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

The description discloses the async nature and the need to poll for completion, but with no annotations, it lacks details on error handling, permissions, rate limits, or response format beyond the id/task_id.

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?

Two sentences, each serving a purpose: first states the action, second provides the critical workflow instruction. No wasted words.

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

Completeness3/5

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

The description covers the basic async pattern and workflow, but given 8 parameters and no output schema, it is incomplete. It does not elaborate on parameter options or the structure of the response beyond the id/task_id.

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?

Schema coverage is 63%, so some parameters are already described. The description adds context that image_url enables image-to-video, which is helpful, but does not explain fps, duration, resolution, aspect_ratio, or negative_prompt.

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 the tool submits an asynchronous video-generation job and contrasts with siblings by mentioning text-to-video and image-to-video, distinguishing it from routara_generate_image and routara_chat.

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 explicitly instructs to poll the returned id/task_id with routara_get_video_status, providing a clear workflow. However, it does not explicitly state when not to use this tool or mention alternatives beyond the sibling list.

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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