xiaohongshu
xiaohongshu
genai-text
Generate text using Google GenAI Gemini models via CLI. Use when the user asks to generate text, get AI responses, create content, write with AI, or use Gemini for text completion.
Full skill instructions
Generate text using the genai-cli text command with Gemini models.
# Basic text generation
uv run genai-cli text "What is the capital of France?"
# With custom model
uv run genai-cli text "Explain quantum computing" --model gemini-3-pro-preview
# Creative writing with temperature
uv run genai-cli text "Write a poem about the ocean" --temperature 0.9
# With system instruction
uv run genai-cli text "Explain this code" --system "You are a senior software engineer"
# Streaming output
uv run genai-cli text "Tell me a long story" --stream
# Save to file
uv run genai-cli text "Generate documentation" --output ./docs.md
uv run genai-cli text [OPTIONS] PROMPT
Options:
--model, -m Model: gemini-2.5-flash (default), gemini-2.5-flash-lite,
gemini-3-pro-preview, gemini-2.0-flash
--temperature, -t Randomness (0.0-2.0, default: 0.7)
--max-tokens, -M Maximum output tokens
--system, -s System instruction/persona
--top-p Nucleus sampling threshold (0.0-1.0)
--top-k Top-k token sampling (1-100)
--stop Stop sequences (can be specified multiple times)
--seed Random seed for reproducibility
--stream Stream output in real-time
--output, -o Save response to file
--json Output as JSON
| Model | Use Case | Notes |
|---|---|---|
gemini-2.5-flash | General text/multimodal | Default - balanced speed/quality |
gemini-2.5-flash-lite | Low latency, high volume | Faster, cheaper |
gemini-3-pro-preview | Complex reasoning/coding | Most capable |
gemini-2.0-flash | Alternative general use | Stable |
Controls randomness. Lower = more deterministic, higher = more creative.
# Factual, deterministic response
uv run genai-cli text "What is 2+2?" --temperature 0.0
# Creative writing
uv run genai-cli text "Write a creative story" --temperature 1.5
Set a persona or context for the model:
# Technical expert
uv run genai-cli text "Review this code" --system "You are a senior security engineer"
# Creative writer
uv run genai-cli text "Write about sunset" --system "You are a poet who loves nature"
# Specific format
uv run genai-cli text "Explain REST APIs" --system "Explain like I'm 5 years old"
Limit or control output length:
# Short response
uv run genai-cli text "Summarize this topic" --max-tokens 100
# Long form content
uv run genai-cli text "Write an essay" --max-tokens 2000
Fine-tune generation with advanced sampling:
# Nucleus sampling (top-p)
uv run genai-cli text "Generate ideas" --top-p 0.9
# Top-k sampling
uv run genai-cli text "Complete this sentence" --top-k 40
# Combined for fine control
uv run genai-cli text "Creative brainstorm" --temperature 0.8 --top-p 0.95 --top-k 50
Stop generation at specific text:
# Stop at markers
uv run genai-cli text "Write a story" --stop "THE END" --stop "---"
Use seed for consistent outputs:
# Same seed = same output
uv run genai-cli text "Generate a name" --seed 42
uv run genai-cli text "Generate a name" --seed 42 # Same result
uv run genai-cli text "Hello"
# Output: Hello! How can I assist you today?
Real-time output as tokens are generated:
uv run genai-cli text "Tell me a story" --stream
# Output appears word by word
Structured output for automation:
uv run genai-cli text "Hello" --json
{
"success": true,
"command": "text",
"data": {
"response": "Hello! How can I assist you today?",
"model": "gemini-2.5-flash"
},
"metadata": {
"temperature": null,
"max_tokens": null,
"stream": false,
"output_file": null
}
}
Save directly to file:
uv run genai-cli text "Generate documentation" --output ./docs.md
# With streaming
uv run genai-cli text "Write a report" --stream --output ./report.txt
uv run genai-cli text "Write a Python function to calculate fibonacci" \
--model gemini-3-pro-preview \
--system "You are an expert Python developer"
uv run genai-cli text "Document this API endpoint" \
--system "You are a technical writer" \
--output ./api-docs.md
uv run genai-cli text "Write a short story about space exploration" \
--temperature 1.2 \
--max-tokens 1000 \
--stream
uv run genai-cli text "Analyze this dataset and provide insights" \
--model gemini-3-pro-preview \
--system "You are a data scientist"
uv run genai-cli text "Translate to Spanish: Hello, how are you?" \
--temperature 0.3
API key must be configured:
uv run genai-cli auth set-key
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