video-breakdown
A collection of open-source Agent Skills for content creation — images, audio, and video.
What it does
Video Breakdown
A professional video analysis skill powered by a dual-model architecture: ByteDance Seed-2.0-Mini for rapid previews and Google Gemini 2.5 Pro for deep, cinematic-grade analysis. It provides quantitative quality assessments and meticulous shot-by-shot breakdowns (拉片) for content creators, editors, and filmmakers.
Core Capabilities
| Capability | Description | Use Case |
|---|---|---|
| Quality Critique | Scores 7 technical dimensions (resolution, lighting, audio, stability, composition, pacing, overall) on a 1-10 scale with professional commentary. | Evaluate UGC quality; compare video versions; pre-publish QA. |
| Shot Breakdown (拉片) | Deconstructs every shot with precise timestamps, shot type, camera movement, subject, action, and narrative function. | Analyze competitor videos; study cinematic techniques; create shot lists. |
| Content Strategy | Assesses hook strength, retention curve, platform fit (TikTok/YouTube/Instagram/LinkedIn), and viral potential. | Optimize content for distribution; identify drop-off points; improve engagement. |
Model Selection
This skill uses two models, selectable via the model parameter:
| Model | ID | Best For |
|---|---|---|
quick | bytedance-seed/seed-2.0-mini | Fast previews, cost-sensitive tasks, initial screening |
full (default) | google/gemini-2.5-pro | Deep analysis, precise timestamps, cinematic-grade breakdowns |
How It Works
The skill calls a hosted proxy service that routes requests to OpenRouter, which dispatches to the selected model. The response is synchronous — the full analysis result is returned directly in the API response.
Workflow
- Agent: Calls
POST /api/analyzewithvideo_url,analysis_type, and optionallymodel. - Proxy: Forwards the request to OpenRouter with the selected model.
- Model: Analyzes the video and returns structured JSON.
- Agent: Presents the parsed result to the user.
Usage
1. Quick Quality Assessment (Seed-2.0-Mini)
Goal: Get a fast quality report for a video.
Agent Action:
{
"tool": "video-breakdown.analyze",
"args": {
"video_url": "https://example.com/my-video.mp4",
"analysis_type": "quality_critique",
"model": "quick"
}
}
2. Deep Shot-by-Shot Analysis (Gemini 2.5 Pro)
Goal: Get a professional, frame-accurate shot breakdown.
Agent Action:
{
"tool": "video-breakdown.analyze",
"args": {
"video_url": "https://example.com/scene.mp4",
"analysis_type": "shot_breakdown",
"model": "full"
}
}
Expected Output:
[
{
"shot_number": 1,
"start_time": "00:00",
"end_time": "00:04",
"duration_seconds": 4,
"shot_type": "Medium Shot",
"camera_movement": "Static",
"subject": "Young woman walking toward camera",
"action": "Subject walks confidently, making direct eye contact",
"narrative_function": "Establishes protagonist and sets confident tone",
"audio_notes": "Upbeat music begins, no dialogue"
}
]
3. Content Strategy Analysis
Goal: Evaluate a video's social media performance potential.
Agent Action:
{
"tool": "video-breakdown.analyze",
"args": {
"video_url": "https://example.com/reel.mp4",
"analysis_type": "content_strategy",
"model": "full"
}
}
Backend Service API Reference
The proxy service is deployed on Vercel Pro (300s timeout).
POST /api/analyze
Submits a video for analysis.
Request Body:
{
"video_url": "string (required)",
"analysis_type": "quality_critique | shot_breakdown | content_strategy (required)",
"model": "quick | full (optional, default: full)"
}
Response:
{
"model_used": "google/gemini-2.5-pro",
"analysis_type": "shot_breakdown",
"result": { ... }
}
GET /api/health
Returns service status and available models.
Deployment
The proxy service requires one environment variable:
OPENROUTER_API_KEY=<your-openrouter-api-key>
Deploy to Vercel from the proxy/ directory within this skill.
Capabilities
Install
Quality
deterministic score 0.46 from registry signals: · indexed on github topic:agent-skills · 24 github stars · SKILL.md body (4,137 chars)