numpy-ufuncs
Universal functions (ufuncs) for vectorization, including reductions, in-place operations, and custom Python-function wrapping. Triggers: ufunc, vectorize, reduce, accumulate, frompyfunc, in-place.
Découvrez les skills testing security framework internals, comparez leurs dépôts et consultez leurs instructions.
Universal functions (ufuncs) for vectorization, including reductions, in-place operations, and custom Python-function wrapping. Triggers: ufunc, vectorize, reduce, accumulate, frompyfunc, in-place.
Structured and record arrays for C-interoperability, binary blob interpretation, and multi-field tabular data handling. Triggers: structured array, record array, compound dtype, multi-field index.
Protocols for cross-library data exchange including DLPack, buffer interfaces, and __array_ufunc__ for overriding NumPy functions. Triggers: DLPack, interoperability, __array_interface__, __array_ufunc__, buffe...
Computer vision library for PyTorch featuring pretrained models, advanced image transforms (v2), and utilities for handling complex data types like bounding boxes and masks. (torchvision, transforms, tvtensor,...
Analyze the competitive and adjacent solution landscape to surface differentiation opportunities.
A custom skill that helps with specific tasks in my project
Generate production-quality Python code for sensor integration, sensor fusion, and perception systems that run in Pyodide (browser). Creates educational code for teaching IMU sensors, LiDAR simulation, depth pe...
Apply appropriate type hints for ML/PyTorch code. Use when adding type annotations to ML code or addressing mypy errors.
Optimize training performance for Kaggle competitions. Use PROACTIVELY when training is slow, GPU memory issues occur, or user asks about performance tuning. Keywords: 遅い, 最適化, OOM, CUDA, batch_size, num_w...
Set up GPU sandboxes for interpretability research. Use when writing setup.py scripts with Sandbox, SandboxConfig, ModelConfig, or create_notebook_session. Provides the exact API for Modal GPU environments - MU...
AI-assisted development workflow with TDD, context management, and incremental implementation. Use when developing features with AI assistance, managing code context for AI tools, implementing features step-by-...
Expert knowledge for building event-driven systems with Composable Rust framework. Use when implementing reducers, designing state machines, working with effects, creating environment traits for dependency inje...
Rust development patterns for video processing, trait abstractions, error handling, and Linux device interaction
Structured performance profiling and optimization skill for identifying and eliminating bottlenecks. Auto-triggers on slowness keywords.
Avoid non-null assertion operator (!) and use type-safe alternatives instead
Deep code and system analysis using the Quantum Cognitive OS. Use when analyzing code, architectures, or complex systems that benefit from multi-dimensional reasoning.
Use Syntax::Keyword::Assert for zero-cost assertions in Perl
Store and export type constraints for Type::Tiny, Moose, Data::Checks, and more
Pure Data reference documentation for audio patch development. Use when writing .pd patches, working with OSC/audio/sampling, or implementing Pure Data code.
Guide for using the Neural DSP Quad Cortex device library in MMD files. Use when the user mentions Quad Cortex, QC, Neural DSP guitar processor, or needs help with preset loading, scene switching, expression co...
Comprehensive F* proof-oriented programming for formal verification including dependent types, refinement types, effect system, SMT solver integration, tactic-based interactive theorem proving, and verified cod...
Use Result::Simple for tuple-based error handling in Perl
Guides performance optimization: atomic clock service, performance monitoring, memory optimization, battery optimization. Use when optimizing performance, monitoring metrics, or improving app efficiency.
Compound Engineering workflow for AI-assisted development. Use when planning features, executing work, reviewing code, or codifying learnings. Follows the Plan → Work → Review → Compound loop where each unit of...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.