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feat: add 11 Venice AI skills as bundled defaults

Skills included:
- venice-chat: Chat with Venice LLM models, vision, reasoning
- venice-chat-benchmark: Benchmark chat models with infographics
- venice-image-gen: Generate images via Venice API
- venice-list-image-models: List available image models
- venice-list-text-models: List available text models
- venice-list-video-models: List available video models
- venice-tts: Text-to-speech via Venice API
- venice-video-generate: Generate videos from text/images
- venice-video-queue: Queue video generation jobs
- venice-video-quote: Get video generation cost quotes
- venice-video-retrieve: Retrieve completed videos

All rebranded from Agent Zero paths to Agent JAE (~/.jae/agent/skills/).
Requires VENICE_API_KEY environment variable.

2026-03-23 18:46:23 +01:00

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Venice Video Queue

Queue videos for generation on Venice.ai. Supports text-to-video and image-to-video.

Requirements

VENICE_API_KEY environment variable

CLI Usage

python ~/.jae/agent/skills/venice-video-queue/scripts/queue_video.py PROMPT [options]

Arguments

Argument	Required	Description
`PROMPT`	Yes	Text prompt describing the video

Options

Option	Short	Default	Description
`--model`	`-m`	`wan-2.5-preview-text-to-video`	Model to use
`--duration`	`-d`	`5s`	Video duration: `5s` or `10s`
`--resolution`	`-r`	`720p`	Resolution: `480p`, `720p`, `1080p`
`--aspect-ratio`	`-a`	None	Aspect ratio e.g. `16:9`, `9:16`, `1:1`
`--negative-prompt`	`-n`	None	Things to avoid in the video
`--image`	`-i`	None	Input image path for image-to-video
`--video`	`-v`	None	Input video path for video-to-video
`--audio`		None	Audio file path to include
`--with-audio`		False	Enable audio generation
`--json`		False	Output result as JSON

Examples

Text-to-Video

python ~/.jae/agent/skills/venice-video-queue/scripts/queue_video.py "A cat playing piano in a jazz club" \
  --duration 5s \
  --resolution 720p \
  --aspect-ratio 16:9

Image-to-Video

python ~/.jae/agent/skills/venice-video-queue/scripts/queue_video.py "Animate this scene with gentle motion" \
  --image /path/to/image.png \
  --model wan-2.5-preview-image-to-video \
  --duration 5s

JSON Output

python ~/.jae/agent/skills/venice-video-queue/scripts/queue_video.py "Cinematic sunset" --json
# Output: {"model": "wan-2.5-preview-text-to-video", "queue_id": "abc123..."}

Output

On success, displays:

✅ Video queued successfully!
   Model:    wan-2.5-preview-text-to-video
   Queue ID: abc123-def456-...

To retrieve, run:
   python retrieve_video.py wan-2.5-preview-text-to-video abc123-def456-...

Retrieval

After queuing, use the venice-video-retrieve skill:

python ~/.jae/agent/skills/venice-video-retrieve/scripts/retrieve_video.py MODEL QUEUE_ID

Common Models

Model	Type	Notes
`wan-2.5-preview-text-to-video`	Text-to-video	Default, good quality
`wan-2.5-preview-image-to-video`	Image-to-video	Animate still images
`veo3.1-full-image-to-video`	Image-to-video	No aspect_ratio support

Programmatic Usage

from queue_video import queue_video, queue_text_to_video, queue_image_to_video

# Text-to-video
result = queue_text_to_video(
    prompt="A cat playing piano",
    duration="5s",
    resolution="720p"
)
print(f"Queue ID: {result.queue_id}")

# Image-to-video
result = queue_image_to_video(
    prompt="Animate this scene",
    image_path="/path/to/image.png"
)

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