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TypeScript
Hybrid

Image to cinematic video (Video AI)

luw_generate_video

Luw.ai Video AI (Motion): animate a design image into a short cinematic video — fly-throughs, dolly moves, drone shots, reveals.

Instructions

Luw.ai Video AI (Motion): animate a design image into a short cinematic video — fly-throughs, dolly moves, drone shots, reveals. Camera motions: A Forward Dolly, Flythrough Cinematic, Return to Empty Room, Lighting and Color Details, Drone flying to center, Dramatic Zoom Out, Reverse Zoom In, Slow Pull Back, Reveal Zoom, Ground to Sky Tilt, Side Tracking Zoom, Aerial Descent. Pass end_image to make the video end on that frame, e.g. the original photo as image and its redesign as end_image for a before → after transition. Takes a few minutes — expect a processing_url to collect with luw_get_result. Costs 10 credits (aria) or 20 (symphony), with or without end_image.

Input Schema

NameRequiredDescriptionDefault
seedNoFix for reproducible results.
imageYesStart frame (a render or photo) (https:// URL, local file path, or data: URI).
engineNoLuw.ai model: aria (default) or symphony (Symphony-3).
promptNoWhat should happen in the video.
end_imageNoOptional end frame the video moves to; use the start frame's aspect ratio (https:// URL, local file path, or data: URI).
camera_motionNoOne of the camera motions listed above, e.g. "Flythrough Cinematic".
enhance_promptNoLet Luw.ai's prompt enhancer expand a short prompt.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.2
    • addedInput schema / properties / end_image
      Added value: +{
+  "description": "Optional end frame the video moves to; use the start frame's aspect ratio (https:// URL, local file path, or data: URI).",
+  "minLength": 1,
+  "type": "string"
+}
  2. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already signal a non-readonly, non-idempotent, open-world operation, so the description correctly reinforces that this is a generation job. It adds valuable behavior beyond annotations: asynchronous processing ('takes a few minutes'), a processing_url to collect with luw_get_result, and credit cost tiers when end_image is used.

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?

Purpose and the result-collection/cost facts are front-loaded, and the camera-motion list, though long, is load-bearing because the schema defers to it. Some density could be trimmed, but little of it is wasted.

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?

With no output schema, the description still covers the return path (processing_url → luw_get_result), timing expectations, pricing, and the end_image workflow, which is everything an agent needs to invoke and poll this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (baseline 3), but the description goes further: it enumerates the 12 valid camera_motion values that the schema only refers to as 'listed above,' and explains the end_image pairing pattern with a worked example. Seed, prompt, and engine are left to the schema, but the enum values would be unknowable without the 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?

States a specific verb and resource: animating a design image into a short cinematic video, with named scope (fly-throughs, dolly moves, drone shots, reveals). This clearly distinguishes it from image-generation siblings like luw_generate_image or luw_render.

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?

Gives concrete usage context (use end_image for a before → after transition, collect results via luw_get_result) and pricing, which helps an agent decide. It does not explicitly compare against alternatives such as luw_image_to_3d or luw_run_model, so it falls short of full when/when-not guidance.

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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