Llm App Patterns

What it does

This skill provides patterns for structuring and interacting with Large Language Model (LLM) applications. It helps developers create more robust, predictable, and maintainable AI agents by offering pre-defined application architectures and interaction flows. The patterns cover common LLM app use cases, promoting best practices in design and implementation.

When to use it

• Building a complex chatbot: Use the skill to structure conversations with clear turns and defined roles for the agent and user.
• Creating an automated content generator: Apply patterns to ensure consistent output format and style across multiple generations.
• Developing a data extraction tool: Leverage predefined flows to reliably extract specific information from unstructured text.
• Designing a personalized recommendation engine: Utilize patterns to manage user context and tailor recommendations effectively.

Key capabilities

• Pre-defined application architectures for LLM apps
• Structured interaction flows
• Best practice implementation guidance
• Common use case coverage

Example prompts

• "Generate a chatbot pattern with a greeting, question prompt, and farewell."
• "Show me the data extraction pattern for extracting product names from online reviews."
• "What's the recommended architecture for building an LLM-powered content summarization tool?"

Tips & gotchas

This skill is most effective when used by developers with some familiarity with LLMs and application design principles. While it provides a solid foundation, customization may be required to fit specific project needs.