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Context Engineering Specialist

context-manager

sickn33/antigravity-awesome-skills

Provides elite guidance on dynamic context management, vector databases, knowledge graphs, intelligent memory, RAG, and multi-agent workflows so AI systems maintain relevant, actionable information across enterprise scenarios.

Conversation Memory System

conversation-memory

sickn33/antigravity-awesome-skills

Persistent LLM conversation memory that manages short-term, long-term, and entity-focused layers to store, retrieve, and consolidate memorable context for smarter conversational AI agents.

CrewAI Multi-Agent Architect

sickn33/antigravity-awesome-skills

Designs and orchestrates role-based multi-agent workflows with CrewAI, defining agent personas, tasks, processes, and memory to run complex structured collaborations and planning pipelines.

CrewAI Multi-Agent Orchestration

crewai-multi-agent

Orchestra-Research/AI-Research-SKILLs

CrewAI orchestrates autonomous multi-agent teams for role-based collaboration, sequential or hierarchical workflows, and production-grade orchestration with memory and tool integrations without LangChain.

Cursor Context Optimization

cursor-context-management

jeremylongshore/claude-code-plugins-plus-skills

Guides Cursor IDE users through context window limits, targeted @-mentions, and conversation resets so AI assistants deliver accurate, fast responses without overflowing memory.

Gemini Automation Workflow

gemini-automation

ComposioHQ/awesome-claude-skills

Automates Gemini operations by walking through Rube MCP/Composio tool discovery, connection management, and execution steps, ensuring schema-aware usage, memory handling, and session reuse for reliable flows.

GGUF Quantization for Efficient LLM Inference

gguf-quantization

Orchestra-Research/AI-Research-SKILLs

This guide details the use of the GGUF format and quantization techniques for running large language models (LLMs) efficiently. GGUF enables optimal inference on consumer hardware, Apple Silicon, and systems requiring CPU-only operation. By compressing models using various K-quant methods (like Q4_K_M), developers can significantly reduce memory footprint and hardware requirements while maintaining high performance.

GPTQ Quantization Guide

Orchestra-Research/AI-Research-SKILLs

GPTQ enables post-training 4-bit quantization for large LLMs, delivering up to 4× memory reduction and 3-4× faster inference with under 2% perplexity loss on consumer GPUs through AutoGPTQ, PEFT, and Transformer integrations.

Landbot Automation Guide

landbot-automation

ComposioHQ/awesome-claude-skills

Guide for automating Landbot operations through Composio's Rube MCP toolkit, covering tool discovery, connection checks, execution patterns, memory/session handling, and schema compliance.

LangChain Architecture Guide

langchain-architecture

sickn33/antigravity-awesome-skills

Comprehensive guide to LangChain architecture, covering agent patterns, chains, memory, document pipelines, and callbacks for building production-ready LLM applications that integrate tools and data sources.

LangChain Error Diagnostics

langchain-common-errors

jeremylongshore/claude-code-plugins-plus-skills

Guide to diagnose and fix LangChain authentication, import, rate limit, parsing, chain, agent, and memory failures, plus debugging tips and tracing resources for integrations.

LangChain SDK Patterns

langchain-sdk-patterns

jeremylongshore/claude-code-plugins-plus-skills

Provides production-ready LangChain SDK patterns for chains, agents, and memory, covering type-safe outputs, fallbacks, async batching, streaming, caching, and structured error handling to keep integrations reliable.

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