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lp-duality
Takes the dual of a linear program (LP). Use when the user provides an LP in LaTeX or markdown and wants its dual, or asks about LP duality transformations.
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testing security framework internals AI Skills
Discover testing security framework internals skills, compare source repositories and read the instructions for each workflow.
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ffi-memory-management
Your approach to handling ffi memory management. Use this skill when working on files where ffi memory management comes into play.
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ffi-bindings
Your approach to handling ffi bindings. Use this skill when working on files where ffi bindings comes into play.
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torch-shape-validator
Add tensor shape validation and documentation to PyTorch code. This skill should be used when working with PyTorch models to ensure tensor shapes are correct and well-documented with inline comments.
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type-hint-adder
Add comprehensive type hints to Python functions and methods, including PyTorch tensor types. This skill should be used when improving code quality through static type checking or when preparing code for mypy v...
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complex-tensor-handler
Handle complex-valued tensors in PyTorch for astronomical imaging applications. This skill should be used when working with Fourier transforms, phase/amplitude representations, and complex arithmetic in PRISM.
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loop-vectorizer
Convert Python loops to vectorized PyTorch tensor operations for performance. This skill should be used when optimizing computational bottlenecks in PyTorch code during Phase 4 performance optimization.
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rust-coder
Rust expert for rainze_core PyO3 module. Use when working on Rust code, performance-critical components, or Python-Rust FFI.
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rust-expert
Expert Rust development including ownership, lifetimes, async, and systems programming
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architect
Expert guidance for GabeDA v2.1 architecture (34 modules) - implementing models, features, debugging 4-case logic, and maintaining the /src codebase.
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netninja-qt-compat
Implement and maintain NET-NiNJA's Qt compatibility logic: auto-select PyQt6 vs PyQt5 based on CPU features (SSE4.1/4.2), add and honor --gui=auto|qt6|qt5, and prevent premature PyQt6 imports that crash on lega...
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skill-with-scripts
A template for skills that include executable code for deterministic operations.
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root-calculator
Performs mathematical root calculations including square root, cube root, and nth roots. Use when user asks to calculate square root, cube root, nth root, or uses keywords like 'sqrt', 'root of', 'calculate roo...
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pytorch-cuda
PyTorch CUDA environment and performance guidance, with emphasis on CUDA 13 toolkit/driver requirements, PyTorch wheel compatibility, and runtime checks. Use when configuring PyTorch on NVIDIA GPUs, debugging C...
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numpy-masked
Masked arrays for robust handling of missing or invalid data, ensuring they are excluded from statistical and mathematical computations. Triggers: masked array, numpy.ma, missing data, invalid values, hard mask...
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unsloth-qlora
Advanced 4-bit quantization techniques using Unsloth and BitsAndBytes for extreme VRAM efficiency (triggers: QLoRA, 4-bit, load_in_4bit, bnb-4bit, VRAM optimization, dynamic quantization).
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pytorch-core
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...
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pytorch-quantization
Techniques for model size reduction and inference acceleration using INT8 quantization, including Post-Training Quantization (PTQ) and Quantization Aware Training (QAT). (quantization, int8, qat, fbgemm, qnnpac...
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torch-compile
Optimize PyTorch with torch.compile (TorchDynamo/Inductor), focusing on compile overhead, graph breaks, and benchmark methodology. Use when speeding up PyTorch models or debugging compile behavior; triggers: to...
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GitHub
pytorch-onnx
Exporting PyTorch models to ONNX format for cross-platform deployment. Includes handling dynamic axes, graph optimization in ONNX Runtime, and INT8 model quantization. (onnx, onnxruntime, torch.onnx.export, dyn...
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GitHub
numpy-core
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...
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GitHub
unsloth-quantization
Utilizing Dynamic 4-bit quantization, FP8 training, and 8-bit optimizers to minimize VRAM usage without sacrificing accuracy. Triggers: quantization, dynamic 4-bit, fp8, bitsandbytes, adamw_8bit, qat.
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pytorch-distributed
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...
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GitHub
numpy-memory
Deep dive into memory layout, including strides, C vs Fortran order, and zero-copy view generation via stride tricks. Triggers: strides, C-order, Fortran-order, memory locality, stride_tricks.
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