wicked-garden-product-imagery-create · git:20260914.d73e4dd · 2026-09-14 · sha256 35c4332d554658be
wicked-garden-product-imagery-create git:20260914.d73e4ddA
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--- name: wicked-garden-product-imagery-create description: | AI-powered image generation from text prompts using multiple providers. Supports 5 providers: cstudio, vertex-curl, OpenAI, Stability AI, Replicate. Use when: "generate image", "create image", "text to image", "new visual" metadata: role: module phases: "clarify,design,review" archetypes: "*" --- # Image Creation AI-powered image generation from text prompts. Supports multiple providers through a unified abstraction layer. ## Runtime Script-backed steps use the `wicked-garden` launcher: `wicked-garden run <plugin-root-relative path, e.g. scripts/…> [args]`. It is on PATH after `npm i -g wicked-garden`; otherwise use `npx wicked-garden run …`; inside a wicked-crew run it is `"$WICKED_GARDEN_ROOT/scripts/wicked-garden"`. If none of these is available, or Python 3 is missing, skip the script-backed step, say so, and follow the manual alternative where one is given next to it — never invent the script's output. Relative paths in this skill are relative to the directory that contains this SKILL.md. ## When To Use This Skill - Generating new images from text descriptions - Creating visual assets for marketing, UI, presentations - Producing multiple variations of a concept - Building visual prototypes from written specifications ## Supported Providers | Provider | Interface | Auth | Best For | |----------|-----------|------|----------| | **cstudio** | CLI binary | `GOOGLE_CLOUD_PROJECT` | Interactive use, rapid iteration | | **vertex-curl** | gcloud + curl | `gcloud auth` | CI/CD, scripted pipelines | | **openai** | REST API | `OPENAI_API_KEY` | Existing OpenAI subscription | | **stability** | REST API | `STABILITY_API_KEY` | Stable Diffusion 3.5 | | **replicate** | REST API | `REPLICATE_API_TOKEN` | Flux models, pay-per-use | ### Provider Detection ```bash # Check which providers are available wicked-garden run skills/product/imagery/scripts/provider.py detect ``` The provider abstraction selects the best available provider automatically. A specific provider can be forced when needed. ## Generation Workflow ``` 1. UNDERSTAND — Clarify the visual intent and requirements 2. CRAFT — Build a high-quality prompt with style and constraints 3. GENERATE — Execute via the provider abstraction 4. REVIEW — Use the review sub-skill to validate output 5. REFINE — Iterate on prompt, parameters, or provider settings ``` ### Step 1: Understand Requirements Before generating, gather: - **Subject**: What is the image of? - **Style**: Photorealistic, illustration, abstract, etc. - **Dimensions**: Aspect ratio (16:9, 1:1, 9:16, etc.) - **Context**: Where will this image be used? - **Constraints**: Brand colors, no text, specific mood ### Step 2: Craft the Prompt Effective prompts follow this structure: ``` [Subject] + [Style/Medium] + [Lighting/Mood] + [Composition] + [Details] ``` Example: "A minimalist office workspace with a single monitor, soft natural side lighting, centered composition, matte finish, neutral color palette" For detailed prompt engineering techniques, see [refs/prompt-engineering.md](refs/prompt-engineering.md). ### Step 3: Generate ```bash # Basic generation (auto-detects best available provider) wicked-garden run skills/product/imagery/scripts/provider.py generate \ --prompt "Your crafted prompt" \ --output ./output/v1.png # Use a specific provider wicked-garden run skills/product/imagery/scripts/provider.py generate \ --prompt "Your crafted prompt" \ --provider openai \ --output ./output/v1.png ``` ### Key Parameters | Parameter | Purpose | Example | |-----------|---------|---------| | `--prompt` | Text description | "A gothic garden at dusk" | | `--aspect-ratio` | Output dimensions | "16:9", "1:1", "9:16" | | `--negative-prompt` | Elements to exclude | "text, watermarks, blur" | | `--sample-count` | Number of variations | 1-4 | | `--seed` | Reproducible results | Any integer | | `--guidance-scale` | Prompt adherence | Higher = more literal | | `--model` | Model selection | "imagen-3.0-generate-001" | ## Detailed References - **Provider APIs and configuration**: [refs/provider-reference.md](refs/provider-reference.md) - **Prompt engineering techniques**: [refs/prompt-engineering.md](refs/prompt-engineering.md) ## Integration With Other Sub-Skills - Use **review** after generation to validate quality and run gates - If modifications are needed, hand off to **alter** for targeted edits - Generation output feeds into the Analyze-Execute-Review-Refine loop