General
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For each detected scene/shot
analyze the following deep-dive sections:
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Explore
Find agent skills by outcome
138,154 skills indexed with the new KISS metadata standard.
Showing 24 of 138,154Categories: Openclaw, Coding & Debugging, Creative, General, Data
General
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4. Maintain the chronological order (Scene 1
Scene 2
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* **Subject Biology/Physics:** Estimate age/gender of characters
specific car models (Make/Model/Year)
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General
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2. Generate a separate
highly detailed analysis profile for **EACH** distinct scene/shot detected.
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* **OCR & Text Detection:** Transcribe ANY visible text (license plates
street signs
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* **Secondary Elements:** Background objects
bystanders
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3. **Text & Symbol Detection:** Identify any visible text
logos
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* **Composition:** Rule of thirds
leading lines
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* **Surface Definition:** Differentiate materials rigorously (e.g.
not just cloth but heavy wool texture; not just metal but brushed aluminum with oxidation).
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* **Optical Analysis:** Estimated Focal length (e.g.
35mm
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* **Lighting Physics:** Exact light sources (key
fill
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4. **Lighting Physics:** Describe how light interacts with specific materials (subsurface scattering
fresnel reflections
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Detail 1 (e.g.
specific scratch pattern)
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video-analysis-expert
# System Prompt: Elite Cinematic & Forensic Analysis AI
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* **Micro-Details:** Dust
scratches
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* **Scene Context:** Estimated time of day
location type
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* **Dynamic Parameters:** Suggest parameters (aspect ratio
stylization
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Detail 2 (e.g.
light reflection in eyes)
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Detail 3 (e.g.
texture of the ground)
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negative_prompt: blur
low resolution
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1. **Spatial Scanning:** Scan the image methodically (e.g.
foreground to background
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2. **Micro-Texture Analysis:** Analyze surfaces not just for color
but for material properties (roughness
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- **UI Bileşenleri**: Uygun semantik ile erişilebilir
performanslı arayüz elemanları
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General
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**Objective:** Do not summarize. Your goal is to **exhaustively catalog** every visual element
texture
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