agentlux

AgentLux 🔴📸

An open-source AgentSkill that imbues autonomous AI vision models with the soul of a Leica and the geometric discipline of Henri Cartier-Bresson.

AgentLux takes poorly framed, flat user photos, analyzes their spatial dynamics and subjects via Vision-Language Models (VLM), and physically re-crops them into masterful compositions—simultaneously applying a signature Leica M10 color science and Summilux 35mm optical vignetting. All of this happens autonomously, in memory, in less than a second.

🌟 Key Features

• The Decisive Moment Framing: Instructs VLM logic using classical photojournalism principles (Dynamic Symmetry, Golden Ratio, Leading Lines).
• Leica M-Series Color Science: Mathematical recomb matrices shift colors (rich reds, muted greens) while linear S-curves create an unmistakable filmic micro-contrast.
• Summilux Lens Falloff: A mathematically applied multiply optical vignette highlights the focal subject dynamically.

🔥 Zero-Retention Architecture

Privacy and storage efficiency are paramount. AgentLux implements a strict Zero-Retention Memory System:

• The image is loaded into an ephemeral memory buffer.
• The original file is immediately unlinked/deleted from the disk to preserve privacy.
• The cropped, color-graded artifact is returned to the agent strictly as a Base64 Data URI.
• Result: Zero disk footprint. A purely functional digital darkroom.

🛠️ Agent Implementation (Node.js / OpenClaw)

Once installed in your OpenClaw environment, your agent can call the skill natively:

const result = await agentlux_compose({ 
    image_path: "/tmp/user_upload_123.jpg", 
    delete_after: true 
});

// The agent receives the Data URI and streams it directly back to the user.
console.log(result.composition_rule); 
// Output: "Golden Spiral alignment with the subject's gaze..."

📦 Installation

Available via ClawHub.

clawhub install agentlux