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llama-farm

The wt skill streamlines AI model deployment, enabling developers to work efficiently with isolated environments and parallel coding sessions, perfect for AI coding workflows

llama-farm

Deploy any AI model, agent, database, RAG, and pipeline locally or remotely in minutes

ebongard

Ein Git-Workflow für den AI-Agent ist eine Sammlung von Regeln und Tools zur Verwaltung von Code und Zusammenarbeit

comet-ml

TypeScript SDK patterns for Opik. Use when working in sdks/typescript.

tylerjrbuell

Composable TypeScript AI agent framework — Effect-TS type safety, 5 reasoning strategies, persistent gateway, real-time streaming, multi-agent A2A

find-xposed-magisk

一个开源的，现代设计的LLMS/人工智能聊天框架。支持多人工智能供应商（OpenAI/Claude 3/Gemini/Ollama/Bedrock/Azure/Mistral/Conspirity），多模态（Vision/TTS）和插件系统。一键免费部署您的私人ChatGPT聊天应用程序。Lobe Chat - an open-source, modern-design LLMs/AI chat framework. Supports Multi AI Providers( OpenAI / Claude 3 / Gemini / Ollama / Bedrock / Azure / Mistral / Perplexity ),

wildcard

caro: fast Rust CLI that turns natural‑language tasks into a safe POSIX command. Built for macOS (MLX/Metal) with a built‑in model; supports vLLM/Ollama/LM Studio. JSON‑only output, safety checks, confirmation, multi‑step goals, devcontainer included.

majiayu000

GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.

VjayRam

Builds and optimizes DSPy (dspy) programs end-to-end: signatures, modules, compilation/optimization, evaluation, and debugging. Use when the user mentions dspy/DSPy, Signature, Module, teleprompter/optimizer, compile, evaluate, few-shot, RAG, tool use, or local LLM endpoints (Ollama/vLLM/LM Studio).

hyperb1iss

Use this skill when building AI features, integrating LLMs, implementing RAG, working with embeddings, deploying ML models, or doing data science. Activates on mentions of OpenAI, Anthropic, Claude, GPT, LLM, RAG, embeddings, vector database, Pinecone, Qdrant, LangChain, LlamaIndex, DSPy, MLflow, fine-tuning, LoRA, QLoRA, model deployment, ML pipeline, feature engineering, or machine learning.