This repository, NVIDIA-NeMo/Skills, is a production-grade framework for evaluating, training, and serving large language models (LLMs), with a strong emphasis on reasoning (math, code, proofs), tool calling, and speech tasks. It provides a CLI (`ns`) that orchestrates distributed pipelines for synthetic data generation, model inference across multiple backends (vLLM, SGLang, TensorRT-LLM, Megatron, OpenAI-compatible APIs), evaluation on 80+ benchmarks (e.g., AIME, SWE-bench, MMLU, BFCL), and reinforcement learning (GRPO, PPO, SFT). The architecture is built around reusable abstractions: configurable dataset preparers, prompt templates, metric collectors, inference servers, code execution sandboxes, and MCP-based tools, all integrated with Slurm/Ray cluster management. While the core is an application toolkit, it also contains numerous research recipes (e.g., OpenMathReasoning, SHERLOC, Nemotron-IMO-TTS) that exemplify its use in generating training data and reproducing published results. The codebase is well-structured with unit tests, GPU integration tests, and Slurm CI, though some components have hardcoded paths and dependencies that limit portability outside NVIDIA's infrastructure.