| name | gemini-text |
| description | Generate text content using Google Gemini models via scripts/. Use for text generation, multimodal prompts with images, thinking mode for complex reasoning, JSON-formatted outputs, and Google Search grounding for real-time information. Triggers on "generate with gemini", "use gemini for text", "AI text generation", "multimodal prompt", "gemini thinking mode", "grounded response". |
| license | MIT |
| version | 1.0.0 |
| keywords | text generation, multimodal, thinking mode, grounding, JSON output, search, reasoning, gemini-3, gemini-2.5 |
Gemini Text Generation
Generate content using Google's Gemini API through executable scripts with advanced capabilities including system instructions, thinking mode, JSON output, and Google Search grounding.
When to Use This Skill
Use this skill when you need to:
- Generate any type of text content (blogs, emails, code, stories)
- Process images with text descriptions or analysis
- Perform complex reasoning requiring step-by-step thinking
- Get structured JSON outputs for data processing
- Access real-time information via Google Search
- Apply specific personas or behavior patterns
- Combine text generation with other Gemini skills (images, TTS, embeddings)
Available Scripts
scripts/generate.py
Purpose: Full-featured text generation with all Gemini capabilities
When to use:
- Any text generation task
- Multimodal prompts (text + image)
- Complex reasoning requiring thinking mode
- Structured JSON output requirements
- Real-time information needs (grounding)
- Custom system instructions/personas
Key parameters:
| Parameter | Description | Example |
|---|
prompt | Text prompt (required) | "Explain quantum computing" |
--model, -m | Model to use | gemini-3-flash-preview |
--system, -s | System instruction | "You are a helpful assistant" |
--thinking, -t | Enable thinking mode | Flag |
--json, -j | Force JSON output | Flag |
--grounding, -g | Enable Google Search | Flag |
--image, -i | Image for multimodal | photo.png |
--temperature | Sampling 0.0-2.0 | 0.7 for creative |
--max-tokens | Output limit | 1000 |
Output: Generated text string, optionally with grounding sources
Workflows
Workflow 1: Basic Text Generation
python scripts/generate.py "Explain quantum computing in simple terms"
- Best for: Simple content creation, explanations, summaries
- Model:
gemini-3-flash-preview (default, fast)
Workflow 2: With System Instruction (Persona)
python scripts/generate.py "How do I read a file in Python?" --system "You are a helpful coding assistant"
- Best for: Domain-specific tasks, expert personas, consistent tone
- Use when: You need specific behavioral constraints
Workflow 3: Complex Reasoning (Thinking Mode)
python scripts/generate.py "Analyze the ethical implications of AI in healthcare" --thinking
- Best for: Complex analysis, step-by-step reasoning, multi-step problems
- Use when: Task requires careful consideration and logical progression
Workflow 4: Structured JSON Output
python scripts/generate.py "Generate a user profile object with name, email, and preferences" --json
- Best for: Data extraction, structured data generation, API responses
- Output: Valid JSON ready for parsing
- Note: Prompt must clearly request JSON structure
Workflow 5: Real-Time Information (Grounding)
python scripts/generate.py "Who won the latest Super Bowl?" --grounding
- Best for: Current events, news, factual information after training cutoff
- Output: Response + grounding sources with citations
- Use when: Accuracy of current information is critical
Workflow 6: Multimodal (Image Analysis)
python scripts/generate.py "Describe what's in this image in detail" --image photo.png
- Best for: Image captioning, visual analysis, image-based Q&A
- Requires: Image file in PNG or JPEG format
- Combines well with: gemini-files for file upload
Workflow 7: Content Creation Pipeline (Batch + Text + TTS)
python scripts/generate.py "Create a 500-word blog post about sustainable energy"
- Best for: High-volume content production, podcasts, audiobooks
Parameters Reference
Model Selection
| Model | Speed | Intelligence | Context | Best For |
|---|
gemini-3-flash-preview | Fast | High | 1M | General use, agentic tasks (default) |
gemini-3-pro-preview | Medium | Highest | 1M | Complex reasoning, research |
gemini-2.5-flash | Fast | Medium | 1M | Stable, reliable generation |
gemini-2.5-pro | Slow | High | 1M | Code, math, STEM tasks |
Temperature Settings
| Value | Creativity | Best For |
|---|
| 0.0-0.3 | Low | Code, facts, formal writing |
| 0.4-0.7 | Medium | Balanced output |
| 0.8-1.0 | High | Creative writing, brainstorming |
| 1.0-2.0 | Very High | Highly creative, varied outputs |
Thinking Budget
| Value | Description |
|---|
| 0 | Disabled (default behavior) |
| 512-1024 | Standard reasoning |
| 2048+ | Deep analysis (slower, more tokens) |
Output Interpretation
Standard Text Output
- Plain text response ready for use
- Check for truncation if max-tokens was set
- May include markdown formatting
JSON Output
- Valid JSON object (use
--json flag)
- Parse with:
import json; data = json.loads(output)
- Verify structure matches your requirements
- Handle potential parsing errors
Grounded Response
When --grounding is used, the script prints:
- Main response text
- "--- Grounding Sources ---" section
- List of sources with titles and URLs
Thinking Mode Output
- May include reasoning steps before final answer
- Longer response times due to thinking process
- Better for tasks requiring careful analysis
Common Issues
"google-genai not installed"
pip install google-genai
"API key not set"
Set environment variable:
export GOOGLE_API_KEY="your-key-here"
export GEMINI_API_KEY="your-key-here"
"Model not available"
- Check model name spelling
- Verify API access for selected model
- Try
gemini-3-flash-preview (most available)
JSON parse errors
- Ensure prompt explicitly requests JSON structure
- Check output for JSON formatting
- Consider using system instruction: "You always respond with valid JSON"
Image file not found
- Verify image path is correct
- Use absolute paths if relative paths fail
- Supported formats: PNG, JPEG
Response truncated
- Increase
--max-tokens value
- Break task into smaller requests
- Use pro models with higher token limits
Best Practices
Performance Optimization
- Use flash models for speed, pro for quality
- Lower temperature (0.0-0.3) for deterministic outputs
- Set appropriate max-tokens to control costs
- Use thinking mode only for complex tasks
Prompt Engineering
- Be specific and clear in your prompts
- Use system instructions for consistent behavior
- Include examples in prompts for better results
- For JSON: specify exact structure in prompt
Error Handling
- Wrap script calls in try-except blocks
- Validate JSON output before parsing
- Handle network timeouts with retries
- Check API quota limits for batch operations
Cost Management
- Use flash models when possible (lower cost)
- Limit max-tokens for simple queries
- Cache results for repeated queries
- Use batch API for high-volume tasks
Related Skills
- gemini-image: Generate images from text
- gemini-tts: Convert text to speech
- gemini-embeddings: Create vector embeddings for semantic search
- gemini-files: Upload files for multimodal processing
- gemini-batch: Process multiple requests efficiently
Quick Reference
python scripts/generate.py "Your prompt"
python scripts/generate.py "Prompt" --system "You are X"
python scripts/generate.py "Complex task" --thinking
python scripts/generate.py "Generate JSON" --json
python scripts/generate.py "Current event" --grounding
python scripts/generate.py "Describe this" --image photo.png
Reference
