image-generation
zc277584121/marketing-skills
Generate illustration images for articles and documentation with Codex-first, OpenAI, and Gemini fallback support.
What is image-generation?
Generate illustration images for blog posts, documentation, and technical articles using a provider-aware workflow. Automatically uses Codex built-in image generation when available, falls back to OpenAI API, then Gemini API. Includes style guidance and prompt templates for architecture diagrams, concept illustrations, and technical visuals.
- Generate illustration images with automatic provider fallback (Codex → OpenAI → Gemini)
- Prepend clean, minimalist style guidance to prompts automatically
- Support multiple aspect ratios (1:1, 3:2, 16:9, 9:16, etc.) and image sizes (512px to 4K)
- Determine optimal output paths based on project structure and existing image directories
- Craft prompts for architecture diagrams, concept illustrations, and technical flows
How to install image-generation
npx skills add https://github.com/zc277584121/marketing-skills --skill image-generation- For Codex path: Codex agent with built-in image_gen tool available
- For OpenAI fallback: OPENAI_API_KEY environment variable set
- For Gemini fallback: GEMINI_API_KEY environment variable set
How to use image-generation
- 1.Clarify image requirements: what to illustrate, language preference, save location, and style preferences
- 2.Select provider path: use Codex built-in if available, otherwise run the script with auto fallback
- 3.Craft the prompt using provided style guidance and prompt writing guidelines; be specific about visual elements and layout
- 4.Run the generation command with desired parameters (aspect ratio, image size, quality, style)
- 5.Verify the result by viewing the generated image and refining the prompt if needed; insert into markdown with appropriate alt text
Use cases
- Generate visual explanations for technical blog articles and documentation
- Create architecture diagrams showing system components and data flow
- Illustrate concept comparisons (e.g., keyword search vs semantic search)
- Produce flow diagrams for workflows and processes
- Generate article headers and visual assets for technical content
- Technical writers and documentation authors
- Content creators writing technical blogs and articles
- Software architects needing visual system diagrams
- Teams building illustrated documentation
image-generation FAQ
Codex built-in image_gen tool is tried first when available. If not available or outside Codex, the script uses OpenAI API if OPENAI_API_KEY is set, then falls back to Gemini if GEMINI_API_KEY is set.
No. The Codex built-in path does not require OPENAI_API_KEY or GEMINI_API_KEY.
Clean, modern color palette with soft tones, minimalist flat illustration style, clear visual hierarchy, professional and polished look suitable for technical articles. No photorealistic rendering or excessive gradients.
Yes, but only if explicitly requested by the user. Default is English for both prompt and in-image text.
Default is 3:2 (landscape), which is ideal for article illustrations. Use 16:9 for social media banners, 9:16 for vertical content, or 1:1 for square images.
Full instructions (SKILL.md)
Source of truth, from zc277584121/marketing-skills.
name: image-generation description: Generate illustration images for articles and documentation with a Codex-first workflow, OpenAI API fallback, and Gemini fallback.
Image Generation Skill
Generate illustration images for blog posts, documentation, and technical articles. The workflow is provider-aware:
- Codex built-in path first — when the current agent is Codex and the built-in
image_gentool is available, use it directly. This path does not requireOPENAI_API_KEY. - OpenAI API fallback — outside Codex, or when the built-in tool is unavailable, use the local script with
OPENAI_API_KEYif present. - Gemini fallback — if OpenAI API generation is unavailable or fails, use the same script with
GEMINI_API_KEYand the existing Gemini image model.
Load provider-specific references only when needed:
- Codex built-in path:
references/codex-built-in.md - OpenAI API fallback:
references/openai-api.md - Gemini fallback:
references/gemini-api.md
When to Use
- User asks to generate an illustration, diagram, concept image, article visual, or documentation visual
- User is writing an article and needs visual explanations for concepts or workflows
- User explicitly asks for a generated raster image
Step 1: Determine the Image Requirements
Before generating, clarify only what is necessary:
- What to illustrate — the concept, architecture, flow, or scene
- Language — default to English for both prompt and text in image. Only use another language if the user explicitly requests it
- Save location — see "Output Path" below
- Style/color preferences — if user has specific needs, use them; otherwise use the default style
Step 2: Select the Provider Path
Path A: Codex Built-In
Use this path when:
- The current agent is Codex
- The built-in
image_gentool is available - The user did not explicitly request API/CLI execution
Read references/codex-built-in.md, generate with the built-in tool, then move/copy the final image into the workspace if it is project-bound.
Path B: Script Auto Fallback
Use this path when:
- The current agent is not Codex
- The built-in tool is unavailable
- The user explicitly asks for API/CLI execution
Run:
python <skill-root>/scripts/generate_image.py \
--prompt "your prompt here" \
--output "/path/to/save/image.png"
The script uses --provider auto by default:
- Try OpenAI API when
OPENAI_API_KEYis set - If OpenAI API fails or is not configured, try Gemini when
GEMINI_API_KEYis set - If neither credential is available, report the missing environment variables
Step 3: Craft the Prompt
Default Style Prefix
The script automatically prepends this style prefix unless --style-prefix or --no-style is used:
Use a clean, modern color palette with soft tones. Minimalist flat illustration style with clear visual hierarchy. Professional and polished look suitable for technical blog articles. No photorealistic rendering. No excessive gradients or shadows.
For the Codex built-in path, include the same style guidance directly in the prompt unless the user requested a different style.
Prompt Writing Guidelines
- Be specific about visual elements, relationships, and layout
- For technical concepts: describe the components and how they connect
- For architecture diagrams: list the layers/components and data flow direction
- For flow diagrams: describe the steps and direction of flow
- If text labels are needed in the image, spell them out explicitly and keep text short
- Default language is English; use another language only when requested
Example Prompts
Architecture diagram:
A system architecture diagram showing: User sends query to an API Gateway,
which routes to a Vector Database labeled "Milvus" and a generation service.
The Vector Database returns relevant documents, which are combined with the
original query and sent to the generation service for final response generation.
Arrows show data flow direction. Each component is a rounded rectangle with
an icon and label.
Concept illustration:
A visual comparison of keyword search vs semantic search. Left side shows
keyword search with exact word matching and highlighted matching words.
Right side shows semantic search with a brain icon understanding meaning
and connecting related concepts with dotted lines. A dividing line separates
the two approaches.
Step 4: Parameters
Default Parameters
| Parameter | Default | Notes |
|---|---|---|
| Provider | auto in script; Codex built-in when available | Codex built-in first, then OpenAI API, then Gemini |
| OpenAI model | gpt-image-2 | Used by script fallback |
| Gemini model | gemini-3.1-flash-image-preview | Used by script fallback |
| Aspect ratio | 3:2 | Landscape, ideal for article illustrations |
| Image size | 1K | Good balance of quality and cost |
| Style | Minimal, clean, soft tones | Auto-prepended by script |
| Language | English | Prompt and in-image text |
Script Options
--provider auto, openai, gemini
--model Provider model ID for the selected provider
--openai-model OpenAI model ID, default gpt-image-2
--gemini-model Gemini model ID, default gemini-3.1-flash-image-preview
--aspect-ratio 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 9:16, 16:9, 21:9, etc.
--image-size 512, 1K, 2K, 4K
--openai-quality low, medium, high, auto
--style-prefix Custom style prefix
--no-style Skip default style prefix
When to Change Defaults
| Scenario | Change |
|---|---|
| Higher quality final asset | --image-size 2K or --openai-quality high |
| Social media banner | --aspect-ratio 16:9 |
| Portrait/vertical image | --aspect-ratio 3:4 or --aspect-ratio 9:16 |
| Square image | --aspect-ratio 1:1 |
| User has their own style | --style-prefix "your style" or --no-style |
| Non-English content | Write prompt in target language |
Step 5: Determine Output Path
Follow this priority order:
Priority 1: Context from Current Conversation
If the user is working on a specific markdown file or article:
- Check where existing images in that article are stored by looking for image references in the
.mdfile - Save the new image in the same directory as the existing images
- Use a descriptive filename that matches the existing naming convention
Example: if the article has , save to the same images/ directory.
Priority 2: Project Image Directory
If no specific article context but working within a project:
- Look for existing image directories:
images/,assets/,static/,img/,figures/ - Save in the most appropriate existing directory
- If none exists, create an
images/directory at the project root or under the relevant content directory
Priority 3: Fallback
If no clear project context:
- Save to the current working directory
- Use a descriptive filename:
concept-name-illustration.png
Step 6: Verify the Result
After generating:
- Read the image file to visually verify it matches the user's request
- If the result is not satisfactory, refine the prompt and regenerate once with targeted changes
- If the image will be inserted into a markdown file, suggest the markdown syntax:
 - Report which provider path was used and where the final file was saved
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