Skip to main content
Glama

generate_video

Generate videos from text prompts, images, or audio using AI models like p-video, wan, and vace. Supports custom durations, resolutions, and aspect ratios.

Instructions

Generate a video from text, image, or audio using Pruna AI.

Args: prompt: Text prompt for video generation model: Model to use (p-video, wan-t2v, wan-i2v, vace) image: Input image URL/path for image-to-video audio: Input audio URL/path for audio-conditioned video duration: Duration in seconds (1-20) resolution: Video resolution (720p or 1080p) aspect_ratio: Aspect ratio (ignored when image is provided) fps: Frames per second (24 or 48) seed: Random seed for reproducible generation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fpsNo
seedNo
audioNo
imageNo
modelNop-video
promptYes
durationNo
resolutionNo720p
aspect_ratioNo16:9

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

Annotations indicate non-read-only, open-world, non-idempotent, non-destructive behavior, but the description adds no behavioral context beyond listing parameters. There is no mention of costs, generation time, or error conditions.

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 and front-loaded with the purpose, followed by a clear parameter list. However, it could be better structured with explicit defaults or grouped parameters.

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?

The description lacks mention of prerequisites (e.g., uploading image/audio files) and does not clarify behavior with multiple inputs. Since output schema exists, return values are not expected, but the tool's complexity warrants more completeness.

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?

With 0% schema description coverage, the description adds meaning by listing parameters and brief explanations (e.g., 'prompt: Text prompt for video generation'), but it does not provide constraints or allowed values for parameters like model or resolution.

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 'Generate a video from text, image, or audio using Pruna AI,' specifying the verb and resource, and implicitly distinguishes from sibling tools like generate_image and transform_video.

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 explicit guidance on when to use this tool vs alternatives such as generate_image or transform_video. The description lists inputs but does not provide decision criteria or mention prerequisites like file uploads.

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/charlesrapp/pruna-mcp-server'

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