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Use when creating Python projects, managing dependencies with uv, configuring pyproject.toml, building packages, or publishing to PyPI - covers project initialization, dependency management, and distribution; N...
Automatically applies when configuring Python project packaging. Ensures proper pyproject.toml setup, project layout, build configuration, metadata, and distribution best practices.
Fast Python environment management with uv (10-100x faster than pip). Triggers on: uv, venv, pip, pyproject, python environment, install package, dependencies.
Python scripting with uv and PEP 723 inline dependencies. Use when creating standalone Python scripts with automatic dependency management.
Builds LaTeX documents using latexmk with live preview and dependency tracking. Use when setting up builds, live preview, or troubleshooting compilation.
Migrate Python projects from setup.py/setup.cfg to pyproject.toml for use with uv. Use when upgrading legacy Python packaging, converting setup.py to modern pyproject.toml format, setting up dependency groups f...
Python development standards including pytest, ruff, black, and mypy. Use when working with Python files, tests, or dependencies.
Guidance for creating Python packages and serving them via a local PyPI server. This skill applies when tasks involve building Python packages (with pyproject.toml or setup.py), setting up local package reposit...
This skill should be used when creating new Python projects or managing Python dependencies. IMPORTANT - uv must ALWAYS be used for any Python-related commands in Python projects (running scripts, installing pa...
Runs Python scripts and manages projects using uv. Use when asked to run a python script, execute python code, run pytest, or install packages. Always uses uv instead of pip or bare python.
Core PyTorch fundamentals including tensor operations, autograd, nn.Module architecture, and training loop orchestration. Covers optimizations like pin_memory and lazy module initialization. (pytorch, tensor, a...
Modern C++ (C++23/C++20) development specialist covering RAII, smart pointers, concepts, ranges, modules, and CMake. Use when developing high-performance applications, games, system software, or embedded system...
Universal functions (ufuncs) for vectorization, including reductions, in-place operations, and custom Python-function wrapping. Triggers: ufunc, vectorize, reduce, accumulate, frompyfunc, in-place.
Integrate multiple programming languages using FFI, native bindings, gRPC, or language bridges. Use when combining strengths of different languages or integrating legacy systems.
Building and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pipelines, model optimization with torch.compile, distributed training, or deploying PyTorch...
Distributed training strategies including DistributedDataParallel (DDP) and Fully Sharded Data Parallel (FSDP). Covers multi-node setup, checkpointing, and process management using torchrun. (ddp, fsdp, distrib...
Fundamental NumPy operations including ndarray creation, dtypes, shape manipulation, and basic operations with a focus on memory alignment and data views. Triggers: numpy, ndarray, dtype, reshape, memory alignm...
Microsoft Pragmatic Rust FFI Guidelines. Use when working with C/C++ interop, creating cdylib, writing unsafe FFI code, or multi-DLL Rust projects.
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in
ML inference latency optimization, model compression, distillation, caching strategies, and edge deployment patterns. Use when optimizing inference performance, reducing model size, or deploying ML at the edge.
LLM inference infrastructure, serving frameworks (vLLM, TGI, TensorRT-LLM), quantization techniques, batching strategies, and streaming response patterns. Use when designing LLM serving infrastructure, optimizi...
Build RAG systems, semantic search, and document clustering with Gemini embeddings API (gemini-embedding-001). Generate 768-3072 dimension embeddings for vector search, integrate with Cloudflare Vectorize, and...
Analyze videos using Google's Gemini API - describe content, answer questions, transcribe audio with visual descriptions, reference timestamps, clip videos, and process YouTube URLs. Supports 9 video formats, m...
Work with state-of-the-art machine learning models for NLP, computer vision, audio, and multimodal tasks using HuggingFace Transformers. This skill should be used when fine-tuning pre-trained models, performing...
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