git clone https://github.com/wells1137/media-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/wells1137/media-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/video-breakdown" ~/.claude/skills/wells1137-media-skills-video-breakdown && rm -rf "$T"
skills/video-breakdown/SKILL.mdVideo 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 |
|---|---|---|
| | Fast previews, cost-sensitive tasks, initial screening |
(default) | | 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
withPOST /api/analyze
,video_url
, and optionallyanalysis_type
.model - 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
POST /api/analyzeSubmits 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
GET /api/healthReturns 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.