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Generate avatar

generate_avatar

Generate a talking-head avatar video from an ACTOR entity and an uploaded audio file. Pass actorEntityId and optionally set avatarQuality. Typically takes a few minutes (longer for longer audio). Tell the user that wait up front. Returns toolExecutionId; get_tool_execution provides status and results with the avatar video file and download URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audioFileIdYesSpeech recording for the actor to lip-sync. Use fileId from an audio upload, list_files, or a succeeded text_to_speech result.
actorEntityIdYesId of a built-in stock actor or an ACTOR entity (vg_enti_...) with an image reference.
avatarQualityNoAvatar generation quality tier. Applies when actorEntityId is provided. Omit to use workspace settings.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoError details when status is failed; otherwise null.
statusNoJob status: pending, running, succeeded, failed, or cancelled.
resultsNoGenerated results with download URLs when succeeded.
toolTypeNoTool name (e.g. GENERATE_IMAGE).
attemptIndexNoCurrent or latest attempt index.
toolExecutionIdYesTool execution id (vg_tool_...).
progressPercentageNoCompletion progress 0-100 (present after polling).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / audioFileId / description
      Previous value: -"Audio file id for the avatar to lip-sync."New value: +"Speech recording for the actor to lip-sync. Use fileId from an audio upload, list_files, or a succeeded text_to_speech result."
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations only supply generic hints (readOnly=false, idempotent=false), so the description carries the real behavioral load: it discloses that generation is slow ('a few minutes, longer for longer audio'), that it is asynchronous, and that results arrive via get_tool_execution. It doesn't state whether re-invocation is billed/duplicated or how failures surface, keeping it from a 5.

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?

Four short sentences, front-loaded with the core action and required inputs, then latency guidance, then the polling handoff. Every sentence contributes something actionable and nothing is redundant.

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?

Despite an output schema existing, the description goes further by explaining the async lifecycle and the ID needed for polling, which is the critical missing link. For a long-running, non-idempotent generation tool with an existing output schema, nothing an agent needs to call and follow up correctly is absent.

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 actorEntityId, audioFileId, and the avatarQuality enum. The description references actorEntityId and avatarQuality but adds no new syntax or constraints beyond the schema's own text, making the baseline 3 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?

States a specific verb and artifact: 'generate a talking-head avatar video from an ACTOR entity and an uploaded audio file.' This clearly differentiates it from siblings like generate_video_clip, voiceover_to_video, and text_to_speech by naming both required input types.

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?

Explains the prerequisite inputs (audio upload / fileId / text_to_speech result) and the follow-up path via get_tool_execution, plus instructs the agent to warn the user about wait time up front. It doesn't explicitly exclude alternatives such as voiceover_to_video, so it stops short of a 5.

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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