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text_to_video

Generate videos from text descriptions using Kling AI models. Submit a prompt to create a task and receive a task ID, status, and output URLs.

Instructions

Create a Kling task on RunAPI (text to video). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptNo
cfg_scaleNo
multi_shotsNo
aspect_ratioNo
callback_urlNo
enable_soundNo
multi_promptNo
kling_elementsNo
negative_promptNo
duration_secondsNo
output_resolutionNo
last_frame_image_urlNo
first_frame_image_urlNo
waitNoPoll until the task reaches a terminal status.
timeout_msNo
poll_interval_msNo
modelNoRunAPI model slug for this model line.
Behavior2/5

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

No annotations are present. The description does not disclose behavioral traits such as cost, asynchronicity, potential rate limits, or side effects of creating a task. It only states the basic action and output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one concise sentence, front-loading key info. However, its brevity omits important details, making it less helpful than it could be.

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

Completeness2/5

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

Given 17 parameters, no output schema, and no annotations, the description is incomplete. It doesn't explain the workflow, parameter usage, or how to interpret results beyond the returns.

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

Parameters2/5

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

With only 12% of parameters described in the schema and zero parameter info in the description, the description fails to add meaning. The user gets no help understanding the 17 parameters beyond the schema's minimal descriptions.

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 clearly states the tool creates a Kling task for text-to-video on RunAPI and specifies the return values (task id, status, output URLs). This distinguishes it from sibling tools like image_to_video, though it does not explicitly differentiate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., image_to_video). No prerequisites, context, or when-not-to-use instructions are provided.

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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