
Video Generation
FreeGenerate high-quality videos from structured prompts.
Free · Opens the source repo
What Video Generation does
The Video Generation skill allows users to create high-quality videos by leveraging structured prompts and a Python script. This skill is particularly useful for developers and designers looking to automate video creation based on specific requirements. By using structured JSON prompts, users can define the content, style, and technical specifications of the video, ensuring that the output meets their expectations.
To use the skill, users begin by identifying the requirements for their video, including subject matter, artistic style, and any reference images that may guide the generation process. The skill supports the inclusion of a reference image, which can serve as a visual guide or be used as the first or last frame of the generated video. This feature enhances the quality of the output, allowing for a more tailored video experience.
Once the requirements are established, users create a structured JSON prompt file that details the video’s content, including character dialogues, audio cues, and camera movements. The final step involves executing a Python script that processes the prompt and generates the video file. The skill streamlines this process, making it accessible for users who may not have extensive programming knowledge.
This skill is ideal for content creators, marketers, and anyone in need of quick video generation without the need for extensive video editing skills. It provides a straightforward method to bring ideas to life through video, making it a valuable tool for those in creative fields.
When to use it
Use this skill when you need to create videos based on specific prompts or reference images, especially for creative projects.
When not to use it
This skill may not be suitable for users looking for advanced video editing features or real-time video manipulation.
What you can build with it
Creating Marketing Videos
Use the skill to generate promotional videos based on specific product details and target audience preferences.
Educational Content Production
Generate instructional videos by providing structured prompts that outline the educational material and visual aids.
Creative Storytelling
Create videos that depict scenes from stories or scripts by defining characters, dialogues, and settings in the JSON prompts.
How to install Video Generation
View source1. Install with the skills CLI
npx skills add bytedance/deer-flow/video-generation --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by bytedanceVideo Generation Skill
Overview
This skill generates high-quality videos using structured prompts and a Python script. The workflow includes creating JSON-formatted prompts and executing video generation with optional reference image.
Core Capabilities
- Create structured JSON prompts for AIGC video generation
- Support reference image as guidance or the first/last frame of the video
- Generate videos through automated Python script execution
Workflow
Step 1: Understand Requirements
When a user requests video generation, identify:
- Subject/content: What should be in the image
- Style preferences: Art style, mood, color palette
- Technical specs: Aspect ratio, composition, lighting
- Reference image: Any image to guide generation
- You don't need to check the folder under
/mnt/user-data
Step 2: Create Structured Prompt
Generate a structured JSON file in /mnt/user-data/workspace/ with naming pattern: {descriptive-name}.json
Step 3: Create Reference Image (Optional when image-generation skill is available)
Generate reference image for the video generation.
- If only 1 image is provided, use it as the guided frame of the video
Step 3: Execute Generation
Call the Python script:
python /mnt/skills/public/video-generation/scripts/generate.py \
--prompt-file /mnt/user-data/workspace/prompt-file.json \
--reference-images /path/to/ref1.jpg \
--output-file /mnt/user-data/outputs/generated-video.mp4 \
--aspect-ratio 16:9
Parameters:
--prompt-file: Absolute path to JSON prompt file (required)--reference-images: Absolute paths to reference image (optional)--output-file: Absolute path to output image file (required)--aspect-ratio: Aspect ratio of the generated image (optional, default: 16:9)
[!NOTE] Do NOT read the python file, instead just call it with the parameters.
Video Generation Example
User request: "Generate a short video clip depicting the opening scene from "The Chronicles of Narnia: The Lion, the Witch and the Wardrobe"
Step 1: Search for the opening scene of "The Chronicles of Narnia: The Lion, the Witch and the Wardrobe" online
Step 2: Create a JSON prompt file with the following content:
{
"title": "The Chronicles of Narnia - Train Station Farewell",
"background": {
"description": "World War II evacuation scene at a crowded London train station. Steam and smoke fill the air as children are being sent to the countryside to escape the Blitz.",
"era": "1940s wartime Britain",
"location": "London railway station platform"
},
"characters": ["Mrs. Pevensie", "Lucy Pevensie"],
"camera": {
"type": "Close-up two-shot",
"movement": "Static with subtle handheld movement",
"angle": "Profile view, intimate framing",
"focus": "Both faces in focus, background soft bokeh"
},
"dialogue": [
{
"character": "Mrs. Pevensie",
"text": "You must be brave for me, darling. I'll come for you... I promise."
},
{
"character": "Lucy Pevensie",
"text": "I will be, mother. I promise."
}
],
"audio": [
{
"type": "Train whistle blows (signaling departure)",
"volume": 1
},
{
"type": "Strings swell emotionally, then fade",
"volume": 0.5
},
{
"type": "Ambient sound of the train station",
"volume": 0.5
}
]
}
Step 3: Use the image-generation skill to generate the reference image
Load the image-generation skill and generate a single reference image narnia-farewell-scene-01.jpg according to the skill.
Step 4: Use the generate.py script to generate the video
python /mnt/skills/public/video-generation/scripts/generate.py \
--prompt-file /mnt/user-data/workspace/narnia-farewell-scene.json \
--reference-images /mnt/user-data/outputs/narnia-farewell-scene-01.jpg \
--output-file /mnt/user-data/outputs/narnia-farewell-scene-01.mp4 \
--aspect-ratio 16:9
Do NOT read the python file, just call it with the parameters.
Output Handling
After generation:
- Videos are typically saved in
/mnt/user-data/outputs/ - Share generated videos (come first) with user as well as generated image if applicable, using
present_filestool - Provide brief description of the generation result
- Offer to iterate if adjustments needed
Notes
- Always use English for prompts regardless of user's language
- JSON format ensures structured, parsable prompts
- Reference image enhance generation quality significantly
- Iterative refinement is normal for optimal results
Providers (Gemini / MiniMax)
Auto-selected by environment variables (CLI unchanged):
GEMINI_API_KEYset → Gemini Veo (default, unchanged).- Only
MINIMAX_API_KEYset → MiniMax video (/v1/video_generation, async 3-step poll/download). - Force with
VIDEO_GENERATION_PROVIDER=gemini|minimax.
MiniMax overrides: MINIMAX_API_HOST (default https://api.minimaxi.com),
MINIMAX_VIDEO_MODEL (default MiniMax-Hailuo-2.3). The first reference image is used
as MiniMax first_frame_image. MiniMax ignores --aspect-ratio (it uses resolution/duration).
Frequently asked questions about Video Generation
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