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USE WHEN: user wants an image prompt, needs creative visual inspiration, asks for design-informed prompts, wants to avoid repetitive AI image generation, or says 'generate a prompt for an image', 'give me a creative image idea', 'make me a unique visual prompt'. DON'T USE WHEN: user wants to generate the image itself (use an image generation tool), wants to edit an existing image, or needs text-only content. EDGE CASES: 'make me an image' → use image generation tool, then optionally this skill for the prompt. 'improve this image prompt' → this skill. 'I keep getting similar AI images' → this skill (solves repetition).\"\n---\n\n# Visual Prompt Engine\n\nGenerate high-quality, diverse image prompts by feeding real visual references into a structured prompt pipeline.\n\n## Problem\n\nAI agents reuse the same visual patterns and clichés when writing image prompts. This skill breaks that cycle by grounding prompts in real, trending design work.\n\n## Architecture\n\n```\nDribbble Scraper → Style Cards → Prompt Generator → Quality Reviewer → Final Prompt\n```\n\n## Quick Start\n\n### 1. Collect Visual References\n\n**Recommended: Browser-based collection** (Dribbble blocks automated requests)\n\nBrowse `https://dribbble.com/shots/popular` with a browser tool (Camofox, Playwright, etc.), collect shot URLs, titles, and image URLs, then save as JSON:\n\n```bash\npython3 scripts/scrape_dribbble.py --method import --import-file manual_shots.json --output data/references.json\n```\n\n**Alternative: RSS/HTML** (may be blocked by WAF)\n\n```bash\npython3 scripts/scrape_dribbble.py --output data/references.json --count 20\n```\n\nThe import JSON format: `[{\"title\": \"...\", \"url\": \"https://dribbble.com/shots/...\", \"image_url\": \"...\"}]`\n\n### 2. Build Style Cards\n\nConvert raw references into style cards:\n\n```bash\npython3 scripts/style_card.py build --input data/references.json --output data/style_cards.json\n```\n\n### 3. Generate Prompts\n\nWhen the user requests an image prompt:\n\n1. Read `data/style_cards.json` for available visual references\n2. Select 1-3 cards relevant to the user's goal\n3. Read `references/prompt-patterns.md` for diverse prompt structures\n4. Read `references/visual-vocabulary.md` for precise design terminology\n5. Compose a prompt combining: user goal + style card elements + varied pattern\n6. Check against recent prompts in `data/prompt_history.json` to prevent repetition\n7. Append the new prompt to history\n\n### 4. Review and Deliver\n\nBefore delivering, verify the prompt:\n- Uses specific visual language (not generic adjectives)\n- References concrete design elements from the style card\n- Follows a pattern different from the last 5 prompts\n- Includes composition, lighting, color palette, and mood\n\n## Style Card Schema\n\nSee `references/style-card-schema.md` for the full schema. A style card contains:\n\n| Field | Description |\n|-------|-------------|\n| `palette` | Hex colors extracted from the design |\n| `composition` | Layout structure (grid, asymmetric, centered, etc.) |\n| `typography` | Font style and weight characteristics |\n| `mood` | Emotional tone (bold, minimal, playful, etc.) |\n| `textures` | Surface qualities (glass, grain, matte, etc.) |\n| `lighting` | Light direction and quality |\n| `source_url` | Original Dribbble shot URL |\n| `tags` | Design categories |\n\n## Prompt Patterns\n\nSee `references/prompt-patterns.md` for 12+ distinct prompt structures that prevent repetition. Rotate through patterns to keep outputs fresh.\n\n## Visual Vocabulary\n\nSee `references/visual-vocabulary.md` for precise design terminology covering color, composition, lighting, texture, and typography. Use these terms instead of generic words like \"beautiful\" or \"nice\".\n\n## Automation (Optional)\n\nSet up a daily cron to refresh visual references:\n\n```bash\n# Run daily to keep references current\npython3 scripts/scrape_dribbble.py --output data/references.json --count 20\npython3 scripts/style_card.py build --input data/references.json --output data/style_cards.json\n```\n\n## Data Directory\n\nThe skill stores working data in `data/`:\n\n```\ndata/\n├── references.json      # Raw Dribbble scrape results\n├── style_cards.json     # Processed style cards\n└── prompt_history.json  # Generated prompts (for deduplication)\n```\n\nCreate the `data/` directory on first run if it does not exist.\n\n## Dependencies\n\nPython 3.9+ with standard library only. 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