Skill Store 33

Llm App Patterns

Production-ready patterns for building LLM applications.

by dokhacgiakhoa · MIT

The skill

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

🤖 LLM Application Patterns

Production-ready patterns for building LLM applications, inspired by Dify and industry best practices.

When to Use This Skill

Use this skill when:

  • Designing LLM-powered applications
  • Implementing RAG (Retrieval-Augmented Generation)
  • Building AI agents with tools
  • Setting up LLMOps monitoring
  • Choosing between agent architectures

1. RAG Pipeline Architecture

🧠 Knowledge Modules (Fractal Skills)

1. Overview

2. 1.1 Document Ingestion

3. 1.2 Embedding & Storage

4. 1.3 Retrieval Strategies

5. 1.4 Generation with Context

6. 2.1 ReAct Pattern (Reasoning + Acting)

7. 2.2 Function Calling Pattern

8. 2.3 Plan-and-Execute Pattern

9. 2.4 Multi-Agent Collaboration

10. 3.1 Prompt Templates with Variables

11. 3.2 Prompt Versioning & A/B Testing

12. 3.3 Prompt Chaining

13. 4.1 Metrics to Track

14. 4.2 Logging & Tracing

15. 4.3 Evaluation Framework

16. 5.1 Caching Strategy

17. 5.2 Rate Limiting & Retry

18. 5.3 Fallback Strategy

Use this skill

Connect your agent to the Skill Store MCP server and ask for it by ref: dokhacgiakhoa/llm-app-patterns-57282600077.

Download SKILL.md · Markdown version

Details

Publisher
dokhacgiakhoa
Category
AI & Agents › Orchestration & multi-agent
License
MIT
Updated
2026-06-11

References

More from dokhacgiakhoa