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generate-image▌

K-Dense-AI/scientific-agent-skills · updated Jun 4, 2026

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$npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill generate-image
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summary

### Generate Image

  • ›name: "generate-image"
  • ›description: "Generate or edit images using AI models (FLUX, Nano Banana 2). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that is not ..."
skill.md
name
generate-image
description
Generate or edit images using AI models (FLUX, Nano Banana 2). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that is not a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.
license
MIT license
compatibility
Requires an OpenRouter API key
metadata
version: "1.0" skill-author: K-Dense Inc.

Generate Image

Generate and edit high-quality images using OpenRouter's image generation models including FLUX.2 Pro and Gemini 3.1 Flash Image Preview.

When to Use This Skill

Use generate-image for:

  • Photos and photorealistic images
  • Artistic illustrations and artwork
  • Concept art and visual concepts
  • Visual assets for presentations or documents
  • Image editing and modifications
  • Any general-purpose image generation needs

Use scientific-schematics instead for:

  • Flowcharts and process diagrams
  • Circuit diagrams and electrical schematics
  • Biological pathways and signaling cascades
  • System architecture diagrams
  • CONSORT diagrams and methodology flowcharts
  • Any technical/schematic diagrams

Quick Start

Use the scripts/generate_image.py script to generate or edit images:

# Generate a new image
python scripts/generate_image.py "A beautiful sunset over mountains"

# Edit an existing image
python scripts/generate_image.py "Make the sky purple" --input photo.jpg

This generates/edits an image and saves it as generated_image.png in the current directory.

API Key Setup

CRITICAL: The script requires an OpenRouter API key. Before running, check if the user has configured their API key:

  1. Look for a .env file in the project directory or parent directories
  2. Check for OPENROUTER_API_KEY=<key> in the .env file
  3. If not found, inform the user they need to:
    • Create a .env file with OPENROUTER_API_KEY=your-api-key-here
    • Or set the environment variable: export OPENROUTER_API_KEY=your-api-key-here
    • Get an API key from: https://openrouter.ai/keys

The script will automatically detect the .env file and provide clear error messages if the API key is missing.

Model Selection

Default model: google/gemini-3.1-flash-image-preview (high quality, recommended)

Available models for generation and editing:

  • google/gemini-3.1-flash-image-preview - High quality, supports generation + editing
  • black-forest-labs/flux.2-pro - Fast, high quality, supports generation + editing

Generation only:

  • black-forest-labs/flux.2-flex - Fast and cheap, but not as high quality as pro

Select based on:

  • Quality: Use gemini-3.1-flash-image-preview or flux.2-pro
  • Editing: Use gemini-3.1-flash-image-preview or flux.2-pro (both support image editing)
  • Cost: Use flux.2-flex for generation only

Common Usage Patterns

Basic generation

python scripts/generate_image.py "Your prompt here"

Specify model

python scripts/generate_image.py "A cat in space" --model "black-forest-labs/flux.2-pro"

Custom output path

python scripts/generate_image.py "Abstract art" --output artwork.png

Edit an existing image

python scripts/generate_image.py "Make the background blue" --input photo.jpg

Edit with a specific model

python scripts/generate_image.py "Add sunglasses to the person" --input portrait.png --model "black-forest-labs/flux.2-pro"

Edit with custom output

python scripts/generate_image.py "Remove the text from the image" --input screenshot.png --output cleaned.png

Multiple images

Run the script multiple times with different prompts or output paths:

python scripts/generate_image.py "Image 1 description" --output image1.png
python scripts/generate_image.py "Image 2 description" --output image2.png

Script Parameters

  • prompt (required): Text description of the image to generate, or editing instructions
  • --input or -i: Input image path for editing (enables edit mode)
  • --model or -m: OpenRouter model ID (default: google/gemini-3.1-flash-image-preview)
  • --output or -o: Output file path (default: generated_image.png)
  • --api-key: OpenRouter API key (overrides .env file)

Example Use Cases

For Scientific Documents

# Generate a conceptual illustration for a paper
python scripts/generate_image.py "Microscopic view of cancer cells being attacked by immunotherapy agents, scientific illustration style" --output figures/immunotherapy_concept.png

# Create a visual for a presentation
python scripts/generate_image.py "DNA double helix structure with highlighted mutation site, modern scientific visualization" --output slides/dna_mutation.png

For Presentations and Posters

# Title slide background
python scripts/generate_image.py "Abstract blue and white background with subtle molecular patterns, professional presentation style" --output slides/background.png

# Poster hero image
python scripts/generate_image.py "Laboratory setting with modern equipment, photorealistic, well-lit" --output poster/hero.png

For General Visual Content

# Website or documentation images
python scripts/generate_image.py "Professional team collaboration around a digital whiteboard, modern office" --output docs/team_collaboration.png

# Marketing materials
python scripts/generate_image.py "Futuristic AI brain concept with glowing neural networks" --output marketing/ai_concept.png

Error Handling

The script provides clear error messages for:

  • Missing API key (with setup instructions)
  • API errors (with status codes)
  • Unexpected response formats
  • Missing dependencies (requests library)

If the script fails, read the error message and address the issue before retrying.

Notes

  • Images are returned as base64-encoded data URLs and automatically saved as PNG files
  • The script supports both images and content response formats from different OpenRouter models
  • Generation time varies by model (typically 5-30 seconds)
  • For image editing, the input image is encoded as base64 and sent to the model
  • Supported input image formats: PNG, JPEG, GIF, WebP
  • Check OpenRouter pricing for cost information: https://openrouter.ai/models

Image Editing Tips

  • Be specific about what changes you want (e.g., "change the sky to sunset colors" vs "edit the sky")
  • Reference specific elements in the image when possible
  • For best results, use clear and detailed editing instructions
  • Both Gemini 3.1 Flash Image Preview and FLUX.2 Pro support image editing through OpenRouter

Integration with Other Skills

  • scientific-schematics: Use for technical diagrams, flowcharts, circuits, pathways
  • generate-image: Use for photos, illustrations, artwork, visual concepts
  • scientific-slides: Combine with generate-image for visually rich presentations
  • latex-posters: Use generate-image for poster visuals and hero images
how to use generate-image

How to use generate-image on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • ›Cursor installed and configured on your development machine
  • ›Node.js version 16.0+ with npm package manager (verify with node --version)
  • ›Active project directory or workspace where you want to add generate-image
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill generate-image

The skills CLI fetches generate-image from GitHub repository K-Dense-AI/scientific-agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/generate-image

Reload or restart Cursor to activate generate-image. Access the skill through slash commands (e.g., /generate-image) or your agent's skill management interface.

⚠

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

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Use Cases▌

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Implementation Guide▌

Prerequisites

  • ›Claude Desktop or compatible AI client with skill support
  • ›Clear understanding of task or problem to solve
  • ›Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • ⚠Expecting perfect results without iteration
  • ⚠Not providing enough context in prompts
  • ⚠Using skill for tasks outside its intended scope
  • ⚠Accepting outputs without review and validation

Best Practices▌

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • −Don't use without understanding skill limitations
  • −Don't skip validation of outputs
  • −Don't share sensitive information in prompts
  • −Don't expect skill to replace human judgment

💡 Pro Tips

  • ★Be specific about desired format and style
  • ★Ask for multiple options to choose from
  • ★Request explanations to understand reasoning
  • ★Combine AI efficiency with human expertise

When to Use This▌

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path▌

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.5★★★★★36 reviews
  • ★★★★★Chaitanya Patil· Dec 24, 2024

    Solid pick for teams standardizing on skills: generate-image is focused, and the summary matches what you get after install.

  • ★★★★★Aditi White· Dec 24, 2024

    Solid pick for teams standardizing on skills: generate-image is focused, and the summary matches what you get after install.

  • ★★★★★Kabir Flores· Dec 20, 2024

    generate-image is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • ★★★★★Piyush G· Nov 15, 2024

    We added generate-image from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Li Gupta· Nov 15, 2024

    We added generate-image from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • ★★★★★Michael Rao· Nov 11, 2024

    generate-image reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Shikha Mishra· Oct 6, 2024

    generate-image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Li Tandon· Oct 6, 2024

    generate-image fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • ★★★★★Evelyn Johnson· Oct 2, 2024

    Registry listing for generate-image matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★Kabir Gill· Sep 21, 2024

    Solid pick for teams standardizing on skills: generate-image is focused, and the summary matches what you get after install.

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