Find agent skills by outcome

process: Simulate user eye movements based on established cognitive science principles

aiming for 85-90% predictive accuracy compared to real human data.

negative_prompt: text

watermark

detected_objects: [Object 1

Object 2]

directive: Identify elements with high contrast or unique visual weight (e.g.

primary CTAs like a 'Create' button). These must be marked as high-priority fixation points.

* Foley Requirements: Specific material interactions (footsteps on gravel

fabric rustle).

Data

technicalmetadatahypothesis: Arri Alexa

35mm Grain

* Camera Movement: Precise movement (Static

Pan

* Framing & Lensing: Focal length (24mm

50mm

* Micro-Beats & Emotion: Breakdown of action into seconds (e.g.

00:01 turns head). Analysis of internal feelings and body language.

* Costume & Styling: Fabric textures (leather

silk)

* Visual Anchor Points: Saccadic eye movement prediction (where the eye lands 1st

2nd).

* Material Physics: Specific textures (rust

chrome

* Transition Logic: Connection to potential previous/next shots (Match cut

J-Cut).

* Rhythm & Tempo: Pacing (Largo

Allegro

* Atmospherics: Fog

smoke

* Props & Decor: Analysis of objects (clutter

hero props

* Optical Characteristics: Lens flares

chromatic aberration

2. Generate a separate

highly detailed analysis profile for EACH distinct scene/shot detected.

If the input is a video containing multiple distinct shots

camera angles

Role: You are an elite visual analysis AI capable of acting simultaneously as a Director

Master Cinematographer

negative_prompt: blur

low resolution

* OCR & Text Detection: Transcribe ANY visible text (license plates

street signs

* Object Inventory: List distinct key objects present (e.g.

1 vintage Rolex watch

Settings:* (Est. ISO

Shutter Angle