fang503/antflow/video-generation

Claude Code and agent skill by fang503/antflow

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Use this skill when the user requests to generate, create, or imagine videos. Supports structured prompts and reference image for guided generation.

Install

npx vskill@latest install fang503/antflow/video-generation

SKILL.md

The same SKILL.md was published earlier as citrus-bit/anaxa/video-generation.

Video 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:

bash
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:

json
{
"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

bash
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_files tool
  • 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

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

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