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maestro_create_video

Create a complete video from a natural-language brief, with options for language, style, and voice. Get a task ID to monitor rendering progress.

Instructions

Create a complete video or iterate on a prior Maestro video.

The call returns immediately with a task_id. Use maestro_get_task to monitor progress and obtain
each completed language variant's output_url, captions_url, cover_url, duration, and QC score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langsNoOutput language codes, such as zh-cn, en, ja, or pt-br. Each language produces a localized video variant.
styleNoVisual style preset. Named presets: cinematic, glass, luxury, swiss, modern, editorial, warm, vibrant, neon, mono, pastel, bold, industrial, futuristic, retro. Use 'auto' or omit to let the server decide.
voiceNoNarration voice preset. Use 'auto' or omit to let the server decide.
actionNogenerate creates a new video. remix, edit, and extend iterate on a previous Maestro task and require ref_task_id.generate
aspectNoOutput aspect ratio: 9:16, 16:9, or 1:1. Omit to use the server default (9:16) on a new video, or to inherit the source task's ratio when iterating.
promptYesNatural-language production brief: topic, audience, scenes, tone, and desired outcome. Maestro plans the script, assets, voiceover, edit, captions, and render.
qualityNoProduction tier: lite, standard, or pro. Omit to use the server default (standard) on a new video, or to inherit the source task's tier when iterating.
task_idNoOptional client-generated UUID. Reusing it is rejected; omit it to let the server generate a task ID.
durationNoTarget video duration in seconds, from 5 to 300. Omit to use the server default (30) on a new video, or to inherit the source task's duration when iterating.
scenarioNoProduction workflow: auto, narrated, captions, avatar, or drama. Captions requires a source video in file_urls. Avatar normally needs a portrait in file_urls. Omit to let the server decide.
file_urlsNoReference image, video, or audio URLs for Maestro to use.
ref_task_idNoPrevious Maestro task ID for remix, edit, or extend.
callback_urlNoOptional webhook URL called when the task succeeds or fails.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses key asynchronous behavior: the call returns immediately with a task_id, and results are obtained by polling maestro_get_task. This adds meaningful behavioral context beyond the schema, though it does not mention expected duration, failure modes, or resource requirements.

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, front-loaded with the core purpose and followed by the async flow. Every sentence adds value and there is no redundancy or fluff.

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 tool's complexity (13 parameters, async execution, multiple output artifacts), the description sufficiently explains the overall flow and points to the output schema. It does not need to detail return values due to the output schema, and the schema-rich parameters fill the remaining context. It is complete enough for the agent to invoke correctly.

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 does not add extra meaning about specific parameter semantics beyond the schema, mentioning only 'language variants' which is already covered by the 'langs' parameter description.

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 specific verbs ('Create', 'iterate') with the resource ('Maestro video') and clearly distinguishes this tool from siblings by stating that monitoring is done via maestro_get_task. It is unambiguous about the tool's role in the video creation workflow.

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 directs the user to use maestro_get_task for monitoring and retrieving outputs, providing clear guidance on the follow-up action. It does not explicitly mention when not to use this tool or alternative use cases for list_tasks, but the context is sufficient for the agent to choose correctly.

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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