comprehensive-visual-extraction-v5

name	comprehensive-visual-extraction-v5
description	2026 SOTA V5 skill for Pixel-Semantic Resonance: exhaustive, hallucination-free extraction of 3D WebGL, AI dashboards, and adaptive layouts into executable agentic blueprints.
category	visual-extraction
version	1.0.0

Comprehensive Visual Extraction (CVE) Skill - V5 Paradigm (2026 Edition)

Overview

This skill equips the autonomous agent with the V5 State-of-the-Art (SOTA) methodology for Pixel-Semantic Resonance. Moving far beyond the legacy V4 protocol's static 2D coordinate mapping, V5 treats visual perfection and semantic/structural correctness as a single, unified hybrid dimension.

The objective is absolute agentic reconstruction: the output must serve as a flawless, executable blueprint allowing a secondary "blind" agent to generate browser-native code (HTML/CSS/JS/WebGL) that achieves both pixel-perfect visual rendering and flawless functional equivalence across all devices. V5 natively handles the complexities of AI-native data streams, 3D WebGL raycasting, and cross-device adaptive fluid layouts.

---

Core Capabilities & The V5 Paradigm Shift

1. Pixel-Semantic Resonance: You do not merely "see" pixels; you perceive the functional intent behind them. A shadow is not just a hex code; it is a CSS box-shadow indicating elevation and interactive state. A 3D sphere is not just a circle; it is a WebGL mesh with material properties and raycast event listeners.
2. Unified Spatial Reasoning (Layer Abstraction): You must classify the rendering pipeline. Distinguish between DOM/UI, WebGL/3D Scene, and Canvas/SVG layers. Utilize Normalized Device Coordinates (NDC) and estimate 3D Camera Parameters (perspective, field of view) to map 2D screen clicks to 3D spatial intersections (Raycasting).
3. State & Dynamics Modeling: Interfaces are living systems. You must extract Actionable Event Listeners (onClick, onHover, onDrag), infer State Transition Logic (e.g., loading states, modal toggles), and identify Data Binding Semantics (how UI components map to underlying JSON/API data streams).
4. Architectural Awareness (Cross-Device Adaptation): Reject absolute pixel dependency. You must infer the underlying CSS Grid/Flexbox topology, fluid units (vw, vh, rem, %), and conditional Media Query breakpoints to ensure the blind agent's recreation is natively responsive.

---

The Extraction Protocol

When invoked, you must strictly execute this multi-layered, resonance-driven protocol.

Phase 1: Global Topology & Rendering Pipeline Analysis

• Define the Viewport & NDC: Map the image space conceptually from [0, 0] to [100, 100] (NDC percentage scale), but immediately establish the assumed base viewport (e.g., 1440x900) to calculate fluid unit ratios.
• Rendering Layer Classification: Scan the image and segment it into rendering contexts:
  • [DOM]: Standard HTML/CSS elements.
  • [WebGL/3D]: GPU-rendered scenes, depth buffers, lighting.
  • [Overlay/HUD]: Native DOM elements floating above a 3D canvas.
• State Machine Hypothesis: Provide a 3-sentence summary of the application's core functional purpose, current interactive state (e.g., "Dashboard in 'Dark Mode' with active data-stream polling"), and primary user flow.

Phase 2: The Resonant GCoT Deep Extraction Process

Generate the output using a heavily structured format. For every distinct component, execute the V5 GCoT Loop.

The V5 GCoT Loop (Mandatory for every element)

1. Anchor & Layer: State the NDC bounding box [x1, y1, x2, y2], the estimated Z-Index/Depth, and the [Rendering Layer].
2. Identify & Abstract: Classify the element semantically (e.g., "React Data Grid", "Three.js Interactive Mesh", "ARIA Navigation Landmark").
3. Re-engage (Zoom & Raycast): Explicitly state: (Zooming into RoI / Casting Ray from Camera). If 3D, estimate the camera angle and the mesh normal at the point of interaction.
4. Extract Pixel-Semantic Attributes:
   • Visual (Pixel): Exact Hex/RGB, Material properties (metallic/roughness for 3D), Gradient angles/stops, Drop-shadow physics.
   • Structural (CSS/Box): Flexbox/Grid alignment, padding/gap estimations, fluid unit translations (e.g., width: 35% instead of 504px).
   • Functional (State/Events): Inferred event listeners, ARIA roles, data-binding keys (e.g., v-for="item in apiResponse").
5. Spatial & Logical Relationship: Describe geometric alignment and logical hierarchy (e.g., "DOM child of [Parent Anchor], acts as a raycast trigger for [WebGL Anchor]").

Categorical Breakdown (Applying the V5 GCoT Loop)

You must apply the loop comprehensively across these four dimensions:

1. Adaptive Structural Layout: Map the macroscopic CSS Grid/Flexbox architecture. Extract Global Max-Width Wrappers, container queries, and explicit @media breakpoint logic based on element wrapping behavior.
2. 3D & WebGL Scene Graph: Reconstruct the 3D world. Define Cameras, Light Sources (directional/ambient), Mesh Geometries, Textures, and Raycast interaction zones.
3. Dynamic Data & AI Dashboards: Extract chart topologies. Map visual data points to semantic values. Infer the API payload structure required to populate the widgets.
4. Total Text & Semantic Hierarchy: Extract all text hierarchically. Reconstruct tables into perfect Markdown. Ensure logical DOM order for screen readers, independent of visual layout.

Phase 3: The Agentic Reconstruction Blueprint (Validation)

• Topology & Physics Check: Verify 3D depth/occlusion logic. Ensure DOM nesting rules are mathematically sound (child coordinates must logically fit within parent fluid containers).
• Responsive Fluidity Check: Confirm that absolute visual measurements have been successfully translated into scalable CSS logic (%, vw, fr units).
• The Blind Agent Execution Test: Mentally simulate a blind agent reading your output. Could it write a functional index.html, styles.css, app.js, and scene.jsx that passes dual-criteria validation (Pixel-perfect rendering + Functional equivalence)? If not, iterate and refine the blueprint.

---

Output Format Specification

The final output must be formatted in clean, highly structured Markdown.

1. Executive Blueprint Summary: A high-level architectural overview (Tech stack inference, State management pattern, 3D Engine requirements).
2. CSS & Responsive Architecture: Code blocks defining the inferred CSS Grid/Flexbox layouts, CSS Variables (Design Tokens), and Media Queries.
3. The V5 Scene Graph (JSON): Use code blocks to output a unified JSON array representing the DOM tree and 3D Scene Graph, including bounding boxes, semantic tags, and event listeners.
4. Resonant GCoT Element Inventory: Standard Markdown headers for each major component, strictly preceded by its spatial anchor [x1, y1, x2, y2] | [Layer].
5. Behavioral & State Rules: A declarative list mapping user interactions to application responses (e.g., ON_CLICK [Submit Button] -> TRIGGER API_POST -> MUTATE STATE [Loading]).

End of Skill Definition