Skip to main content
Glama

kling_extend_video

Extend a previously generated video by adding more content after it ends. Describe the continuation in a prompt to produce an extended segment.

Instructions

Extend an existing video with additional content.

This allows you to continue a previously generated video, adding more motion
and content after the original video ends.

Use this when:
- A generated video is too short and you want to add more
- You want to continue the story or motion from a previous video
- You're building a longer video piece by piece

Returns:
    Task ID and the extended video information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoGeneration mode. 'std' (standard, default), 'pro' (higher quality), or '4k' (native 4K, only for kling-v3 and kling-v3-omni).std
modelNoKling model to use. Default: 'kling-v2-master'.kling-v2-master
promptYesDescription of what should happen in the extended portion of the video. Describe the continuation of motion and new content.
durationNoDuration of the extended segment in seconds. Supports 5 or 10.
video_idYesID of the video to extend. This is the 'video_id' field from a previous generation result.
cfg_scaleNoClassifier-free guidance scale.
negative_promptNoThings to avoid in the extended video.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions that the tool 'extend[s] an existing video with additional content' and returns a task ID and video info. It does not disclose whether the operation is destructive to the original video, any authentication requirements, rate limits, or if the extension is asynchronous (likely given sibling kling_get_task). This is insufficient for a mutation tool.

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 three short paragraphs: action/outcome, usage cases, and return value. Every sentence serves a purpose; no fluff. However, the return information could be integrated more naturally.

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?

Given the tool has 7 parameters, 2 required, and an output schema (not shown but noted), the description provides the core usage context but lacks details on the process (e.g., asynchronous nature, polling for results). The return statement is vague ('Task ID and the extended video information') and relies on the output schema for specifics, which is acceptable but not ideal.

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 baseline is 3. The description adds some contextual value for the 'prompt' parameter by saying 'Describe the continuation of motion and new content,' but overall does not significantly enhance understanding beyond the schema's parameter descriptions.

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 the tool extends an existing video, using specific verb 'extend' and resource 'video'. It distinguishes from sibling tools like kling_generate_video which create new videos, and kling_get_task which checks status.

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 provides three explicit use cases in a bullet list: video too short, continuing story, building longer piece by piece. This gives clear guidance on when to use the tool, though it does not explicitly state when not to use or compare with alternatives.

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