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Lip Sync

lip-sync

Sync video with audio for lip movements. Takes a video and audio file and syncs the lip movements to match the audio. Returns a request ID that can be used with fetch-video to retrieve results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
webhookNoURL to receive webhook notification when processing completes.
model_idYesThe model ID to use for lip sync.
track_idNoCustom tracking ID for the request.
init_audioYesURL or base64 string of the audio file to sync lips with.
init_videoYesURL or base64 string of the input video containing the face to sync.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

With only openWorldHint=true declared, the description usefully discloses the asynchronous execution pattern: a request ID is returned and must be redeemed via fetch-video, and the webhook parameter signals optional completion notification. It still omits processing duration, failure behavior, and any auth or cost considerations.

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?

Three short sentences, front-loaded with the core action and the return/retrieval flow. Sentence one and two slightly overlap, but nothing is wasted and the async contract comes before supporting detail.

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

Completeness3/5

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

For an async generation tool with no output schema, the description adequately covers the call-then-fetch lifecycle. It stops short of guidance on choosing model_id, input size or format limits, or what happens on failure, which an agent would need to call this reliably.

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 all five parameters (including model_id, init_video, init_audio) are already documented in the schema. The description adds no format, size, or model-selection detail beyond what the schema provides, making the baseline 3 appropriate.

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?

The description states a specific verb and resource: syncing video lip movements to an audio track. It is clear what the tool produces, but it does not distinguish itself from the closely related 'dubbing' sibling, which an agent could easily confuse it with.

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?

Usage is implied rather than stated: it says the tool takes a video plus audio and returns a request ID for fetch-video, which routes the agent to the retrieval sibling. There is no explicit when-to-use vs when-not guidance or any mention of alternatives such as dubbing.

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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