Skip to main content
Glama

kling_generate_motion

Animate a character image by transferring motion from a reference video. Extract movements from a video and apply them to a static photo.

Instructions

Transfer motion from a reference video to a character image.

This tool enables character animation by extracting motion from a video
and applying it to a static character image.

Use this when:
- You want to animate a character image using motion from a video
- You want to create a dance or movement video from a still photo
- You need to transfer specific movements to a character

Returns:
    Task ID and motion generation information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
image_urlYesURL of the character image to animate. The character in this image will be animated with the motion from the reference video.
video_urlYesURL of the reference video providing the motion. The character movements from this video will be transferred to the image.
character_orientationNoOrientation of the character. 'image' (default) uses the orientation from the character image, 'video' uses the orientation from the reference video.image
modeNoGeneration mode. 'std' (standard, default) for faster generation, 'pro' for higher quality.std
promptNoOptional text description to guide the motion transfer. Use to add details about the desired output.
keep_original_soundNoWhether to keep the original sound from the reference video. Options: 'yes' or 'no'. Default depends on API.
callback_urlNoWebhook callback URL for asynchronous notifications.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It explains the core behavior (extracting and applying motion) and mentions return value (Task ID and motion information). However, it lacks details on async processing, polling, error states, or auth requirements. The schema covers parameters well, but the description adds minimal extra behavioral context.

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?

The description is concise with 4 sentences plus a bulleted list. It is front-loaded with purpose and use cases. The 'Returns' section adds value. Could be slightly streamlined but overall well-structured without verbosity.

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 has 7 parameters (2 required), enums, and an output schema, the description provides adequate context: purpose, use cases, return type. It lacks guidance on async behavior, callback usage, or error handling, which would improve completeness for a generation tool. Still, it covers the essential aspects.

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%, and the schema already provides detailed explanations for all 7 parameters. The description does not add significant meaning beyond the schema; it only implicitly references image_url and video_url in the purpose statement. Baseline of 3 is 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?

The description clearly states 'Transfer motion from a reference video to a character image' using specific verb+resource. It distinguishes from sibling tools like kling_generate_video and kling_generate_video_from_image by focusing on motion transfer from video to a static image.

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?

The description includes a 'Use this when' list with three clear use cases (animating character image, creating dance/movement video, transferring specific movements). While it does not explicitly mention when not to use or list alternatives, the guidance is clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AceDataCloud/KlingMCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server