Skill: itsmebasil/pattern-skills (version 1.0.0)

--- name: Pattern Jewellery Automation description: Automates jewellery product marketing using Google Vertex AI (Gemini and Imagen) and Google Drive. --- # Pattern Jewellery Automation Skill ## Overview This skill automates the creation of high-end marketing content for Pattern Jewellery products. It orchestrates a sophisticated multi-agent pipeline: securely ingesting raw product photos, generating lifestyle and studio images via Imagen 3, writing SEO-optimized copy via Gemini 1.5 Pro, and systematically organizing the final assets in Google Drive. --- ## 📥 Input Schema The skill expects a trigger payload with the following fields: - `product_image` (String): URL or base64 string of the raw product photograph. - `product_details` (Object): - `name`: Product title (e.g. "Diamond Blue Sapphire Ring") - `sku`: Unique identifier (e.g. "R4389") - `category`: Organization category (e.g. "rings") - `material`: Composition (e.g. "18K white gold, 0.32ct diamond") - `price_now`: Current retail price (e.g. 4455) - `description`: Core design breakdown. ## 📤 Output Schema - `model_image_url`: Link to the generated lifestyle model image. - `product_image_url`: Link to the generated product-only image. - `caption`: Formatted Instagram caption highlighting the luxury aesthetic. - `hashtags`: Array of 20 optimized tags. - `drive_link`: Public/Internal Google Drive folder URL hosting all generated assets. --- ## ⚙️ Workflow Execution Steps ### 1. Vision & Prompt Generation (Gemini 1.5 Pro) The system visually analyzes the `product_image` alongside the `product_details` to determine design intricacy, materials, and aesthetic quality. It then outputs two strictly constrained prompts: * **Model Prompt (Max 120 Tokens):** A lifestyle photograph prompt targeting the Gulf luxury market. It details an elegant model wearing the piece in an upscale interior (e.g., modern Dubai), with specific studio lighting and bokeh settings. * **Product Prompt (Max 120 Tokens):** A premium product-only photography prompt placing the piece on luxury backgrounds (e.g., white Carrara marble, deep navy velvet) equipped with three-point studio lighting and macro lens specs. ### 2. Parallel Image Generation (Imagen 3) Using Google Vertex AI, this step dispatches parallel requests: * Generates the `model_image` (1 sample, ultra quality, 4:5 aspect ratio, adult generation allowed). * Generates the `product_image` (1 sample, ultra quality, 1:1 aspect ratio, tack-sharp). ### 3. Parallel Content Generation (Gemini 1.5 Pro) Concurrently with the image rendering, the LLM drafts an engaging Instagram caption matching Pattern Jewellery's aspirational and traditional-modern fusion tone. It seamlessly integrates the price point and structural details, returning the copy alongside a 20-tag hashtag package. ### 4. Storage & Compilation (Google Drive) All final image bytes (`.jpg`) and text output (`.txt`) are piped into the Google Drive API. They are systematically uploaded into a structured directory constraint: `/Pattern_Jewellery/{category}/{sku}/`. --- ## 🧠 Memory Rules & State Management This skill utilizes a persistent, 4-field memory map to iteratively improve generation over time based on user feedback. The core keys are: - `style`: Default is "editorial" - `tone`: Default is "aspirational-luxury" - `background_preference`: Default is "white-marble" - `top_performing_caption`: Cached high-performing copy for tone-matching. *These variables dynamically inject into the prompt generation templates (Step 1).* ## ⚡ Caching Protocol To minimize unnecessary GPU execution costs: 1. Incoming images are hashed (SHA-256 or pHash). 2. Lookups occur against a Redis/Local cache mapping. 3. If the exact same image and metadata payload are received within the TTL window (30 days), the pipeline bypasses Gemini/Imagen entirely and immediately returns the cached Google Drive URL. ## 📂 Bundled Files - `jewellery_openclaw_skill.json`: The core JSON pipeline graph mapped to OpenCLAW UI. - `jewellery_openclaw_skill.py`: Background FastAPI worker capable of executing the pipeline outside of OpenCLAW. - `pattern_jewellery_openclaw_system.html`: Front-end architectural diagram and design blueprint.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)