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gmh5225

ai-llm-skills-guide

by @gmh5225 in AI & LLM
2
0
# Install this skill:
npx skills add gmh5225/awesome-skills --skill "ai-llm-skills-guide"

Install specific skill from multi-skill repository

# Description

Guide for AI Agents and LLM development skills including RAG, multi-agent systems, prompt engineering, memory systems, and context engineering.

# SKILL.md

name: ai-llm-skills-guide
description: Guide for AI Agents and LLM development skills including RAG, multi-agent systems, prompt engineering, memory systems, and context engineering.

AI Agents & LLM Development Skills

Scope

Use this skill when:

  • Finding or adding AI/LLM related skills
  • Understanding agent architecture patterns
  • Working with RAG, embeddings, or vector databases
  • 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

  • Context fundamentals: What context is and why it matters
  • Context degradation: Lost-in-middle, poisoning, distraction patterns
  • Context compression: Summarization, trimming strategies
  • Context optimization: Caching, masking, compaction

Multi-Agent Patterns

  • Orchestrator pattern
  • Peer-to-peer collaboration
  • Hierarchical delegation
  • Tool-using agents

Where to Add in README

  • Agent frameworks: AI Agents & LLM Development
  • RAG tools: AI Agents & LLM Development or Data & Analysis
  • Observability: AI Agents & LLM Development
  • 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

  1. Modular design: Separate retrieval, generation, and orchestration
  2. Evaluation: Include benchmarks and test cases
  3. Cost awareness: Document token usage and API costs
  4. Fallback strategies: Handle API failures gracefully
  5. Streaming: Support streaming responses where possible

Full Resource List

For more detailed skill resources, complete link lists, or the latest information, use WebFetch to retrieve the full README.md:

https://raw.githubusercontent.com/gmh5225/awesome-skills/refs/heads/main/README.md

The README.md contains the complete categorized resource list with all links.

# Related Skills

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

⚡ Amp 🚀 Antigravity 🤖 Claude Code 🦀 Clawdbot 📝 Codex ▶️ Cursor 🤖 Droid 💎 Gemini CLI 🐙 GitHub Copilot 🪿 Goose 📊 Kilo Code 🔧 Kiro CLI 💻 OpenCode 🦘 Roo Code 🌲 Trae 🏄 Windsurf

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.