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