home / skills / lofcz / llmtornado / llmtornado-tutorial-generator
/src/LlmTornado.Tests/Static/Files/Skills/llmtornado-tutorial-generator
This skill generates comprehensive LlmTornado API tutorials formatted for Medium, including structure, code examples, explanations, and best practices for
npx playbooks add skill lofcz/llmtornado --skill llmtornado-tutorial-generatorReview the files below or copy the command above to add this skill to your agents.
---
name: llmtornado-tutorial-generator
description: Generates comprehensive code tutorials on LlmTornado API formatted for Medium publication with examples, explanations, and best practices.
---
## Tutorial Generation Workflow
Copy this checklist and track your progress:
```
LlmTornado Tutorial Generation Progress:
- [ ] Step 1: Identify tutorial topic and scope
- [ ] Step 2: Structure tutorial outline
- [ ] Step 3: Generate code examples
- [ ] Step 4: Add explanations and best practices
- [ ] Step 5: Format for Medium publication
- [ ] Step 6: Save to local file
```
## **Step 1: Identify tutorial topic and scope**
Determine the specific aspect of LlmTornado API to cover:
- Basic setup and authentication
- Specific API endpoints (chat completions, embeddings, etc.)
- Advanced features (streaming, function calling, etc.)
- Integration patterns
- Error handling and best practices
- Performance optimization
Ask the user if a specific topic isn't provided:
- What LlmTornado API feature should be covered?
- What's the target audience level (beginner, intermediate, advanced)?
- Are there specific use cases to demonstrate?
## **Step 2: Structure tutorial outline**
Create a comprehensive outline following Medium best practices:
### Standard Structure:
1. **Title** - Catchy and SEO-friendly
2. **Introduction** - Hook and overview (2-3 paragraphs)
3. **Prerequisites** - Required knowledge and tools
4. **Setup Section** - Installation and configuration
5. **Core Concepts** - Theory and explanation
6. **Hands-on Examples** - Step-by-step code demonstrations
7. **Best Practices** - Tips and recommendations
8. **Common Pitfalls** - What to avoid
9. **Conclusion** - Summary and next steps
10. **Resources** - Links and references
## **Step 3: Generate code examples**
Create working, production-ready code examples:
### Code Example Guidelines:
- Use proper code formatting with language tags
- Include comments explaining each section
- Show both synchronous and async patterns where applicable
- Demonstrate error handling
- Use realistic use cases
- Keep examples concise but complete
- Include expected output or responses
### Example Code Block Format for Medium:
```python
# Description of what this code does
import llmtornado
# Initialize the client
client = llmtornado.Client(api_key="your_api_key")
# Your implementation here
```
## **Step 4: Add explanations and best practices**
For each code example, provide:
- **What it does** - Clear explanation of functionality
- **Why it matters** - Use cases and benefits
- **How it works** - Step-by-step breakdown
- **Pro tips** - Expert recommendations
- **Security considerations** - API key management, etc.
### Best Practices to Include:
- API key security and environment variables
- Rate limiting and retry logic
- Error handling strategies
- Logging and monitoring
- Cost optimization
- Testing approaches
## **Step 5: Format for Medium publication**
Apply Medium-specific formatting:
### Formatting Rules:
1. **Headings**: Use # for title, ## for main sections, ### for subsections
2. **Code Blocks**: Use triple backticks with language identifier
3. **Inline Code**: Use single backticks for `variable_names` and `function_calls()`
4. **Emphasis**: Use *italics* for emphasis, **bold** for important points
5. **Lists**: Use - or * for bullet points, 1. 2. 3. for numbered lists
6. **Quotes**: Use > for important callouts or tips
7. **Links**: Use [text](url) format
8. **Images**: Use  if applicable
### Medium Style Guidelines:
- Keep paragraphs short (2-4 sentences)
- Use subheadings every 3-4 paragraphs
- Add callout boxes for important notes
- Include a compelling opening hook
- End with actionable next steps
- Aim for 1500-2500 words for optimal engagement
## **Step 6: Save to local file**
Save the generated tutorial to a local markdown file:
### File Naming Convention:
`llmtornado-tutorial-[topic]-[date].md`
Example: `llmtornado-tutorial-chat-completions-2024-01-15.md`
### File Structure:
```
/projects/llmtornado-tutorials/
├── llmtornado-tutorial-[topic].md
└── examples/
└── [topic]-example.py
```
### Save both:
1. The complete Medium-formatted tutorial (markdown)
2. Standalone code examples (Python files)
## Additional Considerations
### LlmTornado API Features to Cover:
- **Chat Completions**: Text generation, conversations
- **Streaming**: Real-time response streaming
- **Function Calling**: Tool integration
- **Embeddings**: Vector representations
- **Model Selection**: Choosing the right model
- **Parameters**: Temperature, max_tokens, top_p, etc.
- **Context Management**: Handling conversation history
- **Rate Limits**: Managing API quotas
### Tutorial Enhancement Options:
- Add diagrams or flowcharts (describe them for Medium's image feature)
- Include performance benchmarks
- Compare different approaches
- Show before/after code improvements
- Add troubleshooting section
- Include testing examples
### SEO Optimization:
- Use keywords naturally in title and headings
- Include meta description (first paragraph)
- Add relevant tags
- Use descriptive subheadings
## Example Usage
When a user requests a tutorial, follow this pattern:
**User**: "Create a tutorial on LlmTornado chat completions"
**Response Process**:
1. Confirm topic and scope
2. Generate full tutorial with:
- Engaging introduction
- Setup instructions
- Multiple code examples
- Best practices
- Troubleshooting tips
3. Save to `/projects/llmtornado-tutorials/llmtornado-tutorial-chat-completions-[date].md`
4. Provide file location and preview
## Quality Checklist
Before finalizing, ensure:
- [ ] All code examples are syntactically correct
- [ ] Explanations are clear and beginner-friendly
- [ ] Medium formatting is properly applied
- [ ] Security best practices are mentioned
- [ ] Error handling is demonstrated
- [ ] Tutorial has a clear flow from simple to advanced
- [ ] Conclusion provides next steps
- [ ] File is saved to local filesystem
- [ ] Both .md and .py files are created
This skill generates complete, Medium-ready tutorials for the LlmTornado API with code examples, explanations, and publication-ready formatting. It guides authors through topic selection, structured outlines, working C# examples, and best practices tailored for agent-oriented .NET projects. Outputs are saved as markdown plus standalone example files for immediate use.
The generator asks or infers the tutorial topic and audience, builds a Medium-friendly outline, and produces step-by-step content including setup, core concepts, and hands-on examples. It creates production-ready code snippets (sync and async patterns), security guidance, and troubleshooting notes, then formats the result for Medium and saves markdown and example files to a local project folder.
Can the skill produce tutorials for different audience levels?
Yes. It prompts for audience level and tailors explanations, examples, and pacing for beginner, intermediate, or advanced readers.
What file outputs are created and where are they saved?
It saves a Medium-formatted markdown file and standalone example files (C#) under /projects/llmtornado-tutorials/ using the naming convention llmtornado-tutorial-[topic]-[date].md.