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@runapi.ai/gemini-omni-mcp

by runapi-ai

text_to_video

Generate videos from text prompts by creating a Gemini Omni task on RunAPI. Returns task ID, status, and output URLs.

Instructions

Create a Gemini Omni task on RunAPI (text to video). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
promptYesVideo generation prompt.
audio_idsNo
timeout_msNo
video_listNo
aspect_ratioNoOutput aspect ratio.
callback_urlNoWebhook URL for terminal Task delivery.
character_idsNo
duration_secondsNo
poll_interval_msNo
output_resolutionNoOutput resolution.
reference_image_urlsNo
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only mentions the return values (task id, status, output URLs) but does not explain asynchronous behavior, polling semantics, or that output URLs may not be immediately available. The default `wait=true` parameter is not mentioned, making the behavior unclear.

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

Conciseness4/5

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

The description is a single concise sentence with no filler or redundancy. It is front-loaded with the core action. However, it is perhaps too brief for a tool of this complexity, though this is more a completeness issue than a conciseness one.

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

Completeness2/5

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

For a tool with 14 parameters, no output schema, and no annotations, this description is severely under-specified. It fails to explain the task lifecycle, the wait/poll behavior, webhook options, or how to interpret the returned status. The description only scratches the surface of what the tool does.

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

Parameters1/5

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

The description provides no parameter information whatsoever. With schema description coverage at only 43%, many parameters (seed, audio_ids, video_list, character_ids, duration_seconds, poll_interval_ms, etc.) remain undocumented in both the schema and the description. The tool description does nothing to compensate for this low coverage.

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 action ('Create') and the resource ('Gemini Omni task') with an explicit parenthetical 'text to video' that distinguishes it from sibling tools like create_audio and create_character. It is specific and immediately understandable.

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

Usage Guidelines3/5

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

The description implies use for text-to-video generation but offers no explicit guidance on when to choose this over create_audio or create_character. No alternatives or exclusion criteria are mentioned, leaving usage context implicit rather than explicit.

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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