Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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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.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
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.
When a user requests video generation, identify:
/mnt/user-dataGenerate a structured JSON file in /mnt/user-data/workspace/ with naming pattern: {descriptive-name}.json
Generate reference image for the video 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.
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.
After generation:
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Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
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Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
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Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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