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Create a video task

create_video

Starts an asynchronous video generation task and returns a task ID; poll status and download the finished video via Modelflare.

Instructions

Starts an asynchronous Modelflare video task and returns its task ID. Poll with get_video_status and save with download_video. Billed to the Modelflare balance by actual usage.

Input Schema

NameRequiredDescriptionDefault
modelYesVideo model ID from list_models.
requestYesRequest body from the model's docs page (from list_models). The model field is set from the model argument.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.3/5.0
Behavior4/5

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

With only openWorldHint in annotations, the description adds meaningful behavior: it is asynchronous, returns a task ID, and is billed to the Modelflare balance by actual usage. It does not cover auth requirements, rate limits, error handling, or idempotency for a task-creation tool.

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?

Three tight sentences: purpose first, then the polling/download workflow, then billing. Each sentence earns its place and there is no redundant restatement of the tool name or schema.

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

Completeness5/5

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

The description covers what the tool returns (task ID), how to proceed afterward (get_video_status, download_video), and the billing model. With full schema coverage for the nested request object and no output schema, this is complete enough for correct invocation and follow-up.

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 description coverage is 100%, and the schema already explains both model and request in detail, including references to list_models and the model's docs page. The description itself adds no parameter-level meaning, so the baseline of 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 states a specific verb and resource: it 'Starts an asynchronous Modelflare video task and returns its task ID.' It also names get_video_status and download_video as follow-up tools, clearly distinguishing this as the task-creation step rather than polling or saving.

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 gives explicit next steps: poll with get_video_status and save with download_video. However, it does not state when this tool should be chosen over siblings like generate_image or list_models, nor does it mention preconditions or exclusions.

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