Generate high-quality images via Gemini models with structured prompts, aspect ratios, and brand validation.
Works with
Supports three Gemini models (gemini-3-pro-image, gemini-2.5-flash-image, gemini-2.5-pro-image) optimized for different quality-speed tradeoffs
Enforces structured prompt format covering subject, style, lighting, mood, composition, aspect ratio, and brand colors to ensure consistency
Includes multi-agent workflow for prompt validation, style verification, and output delivery a
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionimage-generationExecute the skills CLI command in your project's root directory to begin installation:
Fetches image-generation from supercent-io/skills-template and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate image-generation. Access via /image-generation in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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AI image generation skill via MCP. Use Gemini models or compatible services to generate high-quality images for marketing, UI, and presentations.
# Check MCP server configuration
claude mcp list
# Check Gemini CLI availability
# gemini-cli must be installed
Required setup:
Write a structured prompt:
**Subject**: [main subject]
**Style**: [style - minimal, illustration, photoreal, 3D, etc.]
**Lighting**: [lighting - natural, studio, golden hour, etc.]
**Mood**: [mood - calm, dynamic, professional, etc.]
**Composition**: [composition - centered, rule of thirds, etc.]
**Aspect Ratio**: [ratio - 16:9, 1:1, 9:16]
**Brand Colors**: [brand color constraints]
| Model | Use case | Notes |
|---|---|---|
gemini-3-pro-image |
High quality | Complex compositions, detail |
gemini-2.5-flash-image |
Fast iteration | Prototyping, testing |
gemini-2.5-pro-image |
Balanced | Quality/speed balance |
# Generate 2-4 variants
ask-gemini "Create a serene mountain landscape at sunset,
wide 16:9, minimal style, soft gradients in brand blue #2563EB"
# Iterate by changing a single variable
ask-gemini "Same prompt but with warm orange tones"
Review checklist:
Final deliverables:
{
"prompt": "serene mountain landscape at sunset...",
"model": "gemini-3-pro-image",
"aspect_ratio": "16:9",
"style": "minimal",
"brand_colors": ["#2563EB"],
"output_file": "hero-image-v1.png",
"timestamp": "2026-01-21T10:30:00Z"
}
Prompt:
Create a serene mountain landscape at sunset,
wide 16:9, minimal style, soft gradients in brand blue #2563EB.
Focus on clean lines and modern aesthetic.
Expected output:
Prompt:
Generate a 1:1 thumbnail of a futuristic dashboard UI
with clean interface, soft lighting, and professional feel.
Include subtle glow effects and dark theme.
Expected output:
Prompt:
Create a LinkedIn banner (1584x396) for a SaaS startup.
Modern gradient background with abstract geometric shapes.
Colors: #6366F1 to #8B5CF6.
Leave space for text overlay on the left side.
Expected output:
Cause: Missing stable style constraints Solution: Add style references and a fixed palette
Cause: Ratio not specified or an unsupported ratio Solution: Provide an exact ratio and regenerate
Cause: Color codes not specified Solution: Specify brand colors via HEX codes
## Image Generation Report
### Request
- **Prompt**: [full prompt]
- **Model**: [model used]
- **Ratio**: [aspect ratio]
### Output Files
1. `filename-v1.png` - [description]
2. `filename-v2.png` - [variant description]
### Metadata
- Generated: [timestamp]
- Iterations: [count]
- Selected: [final choice]
### Usage Notes
[Any notes for implementation]
| Agent | Role |
|---|---|
| Claude | Prompt structuring, quality verification |
| Gemini | Run image generation |
| Codex | File management, batch processing |
#image-generation #gemini #mcp #design #creative #ai-art
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
supercent-io/skills-template
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
Useful defaults in image-generation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
image-generation has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: image-generation is focused, and the summary matches what you get after install.
image-generation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
image-generation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
image-generation has been reliable in day-to-day use. Documentation quality is above average for community skills.
image-generation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for image-generation matched our evaluation — installs cleanly and behaves as described in the markdown.
image-generation reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added image-generation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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