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Prompt to video

prompt_to_video_clip

Generate one short AI video clip from a prompt inside a new editable project. Returns workflowRunId, projectId, and projectUrl; poll get_workflow_run for status and downloadUrl after auto-export.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the short video clip.
qualityNoVideo generation quality. Omit to use workspace settings.
autoExportNoWhen true (the default), the run stays in progress until an MP4 is ready. Use downloadUrl from the result. Set false only if you will call remix_project and then export_project yourself.
aspectRatioNoOutput aspect ratio as width:height units (not pixels). Example: { width: 16, height: 9 }.
imageFileIdsNoReference images to guide the generated appearance. Use fileId values from upload_file, get_file, or list_files.
durationSecondsNoRequested clip playback duration in seconds.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoError details when status is failed; otherwise null.
statusNoJob status: pending, running, succeeded, failed, or cancelled.
exportIdNoExport id when autoExport succeeded (vg_expo_...).
projectIdYesProject created for this exact workflow attempt (vg_proj_...). A retry creates a different project.
projectUrlYesDeep link to the project created for this exact workflow attempt. Keep it paired with workflowRunId; a retry returns a new URL.
downloadUrlNoSigned MP4 download URL when autoExport succeeded. Give this to the user.
attemptIndexNoCurrent or latest attempt index.
exportFileIdNoFile id of the rendered MP4 when autoExport succeeded.
workflowTypeNoWorkflow type (present after polling).
workflowRunIdYesWorkflow run id (vg_work_...). Keep it paired with this response's projectId and projectUrl; a retry returns a new tuple.
remixActionIdsNoRemix action ids from the start response (empty when none requested).
progressPercentageNoCompletion progress 0-100 (present after polling).
downloadUrlExpiresAtNoUnix expiry for downloadUrl.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / durationSeconds / description
      Added value: +"Requested clip playback duration in seconds."
    • changedInput schema / properties / imageFileIds / description
      Previous value: -"Optional reference image file ids."New value: +"Reference images to guide the generated appearance. Use fileId values from upload_file, get_file, or list_files."
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations declare a non-read-only, non-destructive, non-idempotent, closed-world mutation, and the description adds meaningful behavior on top: it creates a new editable project and is asynchronous, requiring polling of get_workflow_run, with auto-export producing an MP4. That async lifecycle and the project side effect are not derivable from the annotations alone.

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 dense sentences with zero waste; the core action is front-loaded and the async follow-up is second. Every clause (new editable project, returned IDs, polling target, auto-export) 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?

For a 6-parameter creation tool with an output schema present, the description covers the async return lifecycle and the auto-export path without needing to restate return values. The remaining gap is sibling selection (generate_video_clip vs. this tool), which is left unresolved.

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%, so the schema already documents prompt, quality, autoExport, aspectRatio, imageFileIds, and durationSeconds in detail, including the autoExport/remix_project interaction. The description adds no parameter-level detail beyond what the schema provides, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb and resource: 'Generate one short AI video clip from a prompt inside a new editable project,' which is specific about scope (single clip, new project). However, it never distinguishes itself from the sibling generate_video_clip, whose name implies a near-identical job, so an agent cannot tell the two apart from the text alone.

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 second sentence gives a clear follow-up pattern ('poll get_workflow_run for status and downloadUrl after auto-export'), which is useful operational guidance. But there is no when-to-use vs. when-not guidance relative to generate_video_clip, script_to_video, storyboard_to_video, or the other video-producing siblings, so selection is left to inference.

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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