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omergocmen
by omergocmen

generate_video

Generates a video project from JSON scenes, supporting text, images, video, audio, components, and subtitles for custom video creation.

Instructions

Creates a video project using the json2video API. Each project can contain multiple scenes, and each scene can contain various elements such as text, images, video, audio, components, HTML, voice, audiogram, and subtitles. See https://json2video.com/docs/api/ for full schema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoUnique identifier for the movie project. If not provided, a random string will be generated.
commentNoA comment or description for the movie project.
cacheNoUse the cached version of the movie if available. Default: true.
client_dataNoKey-value pairs included in the response and webhooks. Used to pass information to later workflow steps.
draftNoIf true, adds a watermark to the movie. Free plans must set draft to true.
qualityNoQuality of the final rendered movie. Use for speed/quality tradeoff.high
resolutionNoPreset resolution. Use "custom" to set width/height manually.custom
widthNoWidth of the movie (pixels). Only if resolution is "custom". Min: 50, Max: 3840.
heightNoHeight of the movie (pixels). Only if resolution is "custom". Min: 50, Max: 3840.
variablesNoGlobal variables for use in templates/components. Variable names: letters, numbers, underscores.
elementsNoGlobal elements not tied to a specific scene. Each element can be of type video, image, text, html, component, audio, voice, audiogram, subtitles.
scenesYesList of scenes in the video. Each scene contains an array of elements.
apiKeyNojson2video API key (optional, can also be set as environment variable JSON2VIDEO_API_KEY)
Behavior2/5

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

With no annotations available, the description carries the full burden of disclosing behavioral traits. It does not mention that video generation is asynchronous, that it returns a project ID, that there may be costs or API limits, or that the process may take significant time. The only external reference is a URL for the full schema, but critical behavioral context is missing.

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 a single sentence plus a link, which is concise. However, it lacks structure: no bullet points, no clear separation of key points. It is not front-loaded with the most critical information (e.g., the required 'scenes' parameter). It is adequate but not well-optimized for quick scanning.

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 the complexity of the tool (13 parameters, deeply nested objects, required scenes) and the absence of an output schema, the description is insufficiently complete. It does not explain the return value, the asynchronous nature, the cost implications, or how to handle the response. The tool relies entirely on external documentation, which is poor practice for an AI agent.

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 coverage is 100% and each parameter has a description, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides. It lists element types but that is also covered in the schema. Thus, it does not improve parameter understanding beyond the structured data.

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 video project using the json2video API and lists the types of elements that can be included (text, images, video, etc.). It effectively communicates the primary purpose. However, it does not differentiate from sibling tools like create_template, which also involves creating something, though the distinction is somewhat implicit.

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?

The description provides no guidance on when to use this tool versus alternatives such as create_template or get_video_status. It does not mention prerequisites, context, or exclusions. The agent receives no help in deciding whether to invoke this tool.

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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