AI Agents & LLM Development Skills
Scope
Use this skill when:
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Finding or adding AI/LLM related skills
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Understanding agent architecture patterns
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Working with RAG, embeddings, or vector databases
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Implementing multi-agent systems
Key Skill Categories
Agent Frameworks
Framework Description
LangGraph Stateful, multi-actor AI applications
CrewAI Role-based multi-agent orchestration
AutoGen Microsoft's multi-agent framework
RAG (Retrieval-Augmented Generation)
Component Skills
Embeddings Text embedding models, chunking strategies
Vector DBs Pinecone, Weaviate, Chroma, Qdrant
Retrieval Hybrid search, reranking, context optimization
Observability & Tracing
Tool Purpose
Langfuse Open-source LLM observability
LangSmith LangChain tracing and debugging
Weights & Biases ML experiment tracking
Memory Systems
Type Description
Short-term Conversation buffer, sliding window
Long-term Vector store persistence, entity memory
Episodic Experience-based memory recall
Context Engineering Skills
Core Concepts
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Context fundamentals: What context is and why it matters
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Context degradation: Lost-in-middle, poisoning, distraction patterns
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Context compression: Summarization, trimming strategies
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Context optimization: Caching, masking, compaction
Multi-Agent Patterns
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Orchestrator pattern
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Peer-to-peer collaboration
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Hierarchical delegation
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Tool-using agents
Where to Add in README
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Agent frameworks: AI Agents & LLM Development
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RAG tools: AI Agents & LLM Development or Data & Analysis
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Observability: AI Agents & LLM Development
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Context engineering: Context Engineering
Key Repositories
sickn33/antigravity-awesome-skills/skills/ ├── langgraph/ ├── crewai/ ├── langfuse/ ├── rag-engineer/ ├── prompt-engineer/ ├── voice-agents/ ├── agent-memory-systems/ └── autonomous-agents/
muratcankoylan/Agent-Skills-for-Context-Engineering/skills/ ├── context-fundamentals/ ├── context-degradation/ ├── context-compression/ ├── multi-agent-patterns/ └── memory-systems/
Best Practices
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Modular design: Separate retrieval, generation, and orchestration
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Evaluation: Include benchmarks and test cases
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Cost awareness: Document token usage and API costs
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Fallback strategies: Handle API failures gracefully
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Streaming: Support streaming responses where possible
Full Resource List
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https://raw.githubusercontent.com/gmh5225/awesome-skills/refs/heads/main/README.md
The README.md contains the complete categorized resource list with all links.