majiayu000/claude-skill-registry - 36ページ

numpy-indexing

Advanced indexing techniques including slicing, fancy indexing, and boolean masks, along with memory implications of views vs. copies. Triggers: indexing, slicing, fancy indexing, boolean mask, np.where, np.ix_.

原文の言語: 英語

numpy-interop

Protocols for cross-library data exchange including DLPack, buffer interfaces, and __array_ufunc__ for overriding NumPy functions. Triggers: DLPack, interoperability, __array_interface__, __array_ufunc__, buffer protocol.

原文の言語: 英語

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.

原文の言語: 英語

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.

原文の言語: 英語

numpy-structured

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.

原文の言語: 英語

nvidia-nemo

NVIDIA NeMo framework for building and training conversational AI models. Use for NeMo Retriever models, RAG (Retrieval-Augmented Generation), embedding models, enterprise search, and multilingual retrieval systems.

原文の言語: 英語

oapply-colimit

oapply operad algebra evaluation via colimits with Specter-style composition patterns

原文の言語: 英語

occlusion-trace-meta-proof

Generate meta-proofs for occluded reasoning traces.

原文の言語: 英語

offline-vs-online-eval

* **Depends on**: None * **Compatible with**: None * **Conflicts with**: None * **Related Skills**: None # Overview Comprehensive guide to offline and online evaluation strategies for AI/ML models, in

原文の言語: 英語

omnihuman1-video

OmniHuman1によるAIアバター・リップシンク動画生成ガイド。 Use when: (1) user says「AIアバター」「リップシンク」「OmniHuman」, (2) user wants talking head videos from images, (3) user mentions「アバター動画」「1枚の画像から動画」. Do NOT use for: 実写動画編集（video-agentを使用）、 アニメ制作（anime-productionを使用）。

openai-whisper

Local speech-to-text with the Whisper CLI (no API key).

原文の言語: 英語

openai-whisper

Conversão local de voz para texto com o Whisper CLI (sem necessidade de chave de API).

原文の言語: 英語

openai-whisper

Local speech-to-text with the Whisper CLI (no API key).

原文の言語: 英語

operad-compose

Operad Composition Skill (PLUS +1)

原文の言語: 英語

output-waehlen

Output wählen im KI-Governance: Diese Output-Weiche für Ki Governance entscheidet, ob Memo, Antrag, Schriftsatz, Tabelle, Risikoampel, Fragenliste oder Mandantenbrief der richtige nächste Schritt ist.

原文の言語: ドイツ語

own

Use when the user asks for a debrief on recent work, wants to check what they actually own versus what AI carried, or asks to be quizzed on their codebase. Triggers on "debrief", "what do I own", "own this", "quiz me on the code". User-invoked only — never…

原文の言語: 英語

pathology-roi-selector

Select and extract regions of interest (ROI) from whole slide images (WSI) for AI training data preparation and pathology research.

原文の言語: 英語

bio-metabolomics-pathway-mapping

Map metabolites to biological pathways using KEGG, Reactome, and MetaboAnalyst. Perform pathway enrichment and topology analysis. Use when interpreting metabolomics results in the context of biochemical pathways.

原文の言語: 英語

pennylane

Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms…

原文の言語: 英語

phase-space-transformation

Coordinate changes preserving dynamics

原文の言語: 英語

photo-content-recognition-curation-expert

Expert in photo content recognition, intelligent curation, and quality filtering. Specializes in face/animal/place recognition, perceptual hashing for de-duplication, screenshot/meme detection, burst photo selection, and quick indexing strategies. Activate on…

原文の言語: 英語

plasma-mind

Plasmoid consciousness detector. Maps Monad-Stokes fluid dynamics to ANY flow system, identifies Birkeland-like current structures, computes plasmoid consciousness thresholds (Psi > phi^{-5}), and extracts Nambu Hamiltonians {H1,H2,H3}=1. The cosmic nervous…

原文の言語: 英語

bio-population-genetics-population-structure

Analyze population structure using PCA and admixture analysis with PLINK and ADMIXTURE. Identify population clusters, assess ancestry proportions, visualize genetic structure, and choose optimal K for admixture models. Use when analyzing population…

原文の言語: 英語

powergraph-gnn-research

Research pipeline for topology-aware GNN representation learning on power grids using the PowerGraph benchmark. Use when (1) building physics-guided GNNs for power flow (PF), optimal power flow (OPF), or cascading failure prediction, (2) implementing…

原文の言語: 英語

predictive-analytics

ML-based estimation patterns, confidence intervals, and predictive modeling. Reference this skill when forecasting costs or time.

原文の言語: 英語

prepare-dataset

Process and validate datasets for training. Use when setting up data pipelines.

原文の言語: 英語

progress-photo-analyzer

Analyze construction site photos to track progress, detect safety issues, and compare against BIM models using computer vision.

原文の言語: 英語

propagators

Sussman/Radul propagator networks for constraint propagation and bidirectional

原文の言語: 英語

protein-phylogeny

Protein (gene) phylogeny inference pipeline: generates a .qmd analysis script that performs alignment, optional trimming, and tree building. Use when building phylogenetic trees from protein sequences, aligning protein families, running IQ-TREE or MAFFT for…

原文の言語: 英語

prove

Formal theorem proving with research, testing, and verification phases

原文の言語: 英語

pymc-modeling

Bayesian statistical modeling with PyMC v5+. Use when building probabilistic models, specifying priors, running MCMC inference, diagnosing convergence, or comparing models. Covers PyMC, ArviZ, pymc-bart, pymc-extras, nutpie, and JAX/NumPyro backends. Triggers…

原文の言語: 英語

pyopenms

Complete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS…

原文の言語: 英語

python-scientific-computing

Python for engineering analysis, numerical computing, and scientific workflows using NumPy, SciPy, SymPy

原文の言語: 英語

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, autograd, nn.Module, optimizer, training loop,…

原文の言語: 英語

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 CUDA setup, or migrating to CUDA 13; triggers:…

原文の言語: 英語

pytorch-deployment

Comprehensive guide for deploying PyTorch models to production, covering export formats, optimization techniques, and deployment patterns.

原文の言語: 英語

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, distributeddataparallel, torchrun, nccl, rank,…

原文の言語: 英語

pytorch-geometric

Library for Graph Neural Networks (GNNs). Covers MessagePassing layers, modular aggregation schemes, and handling large graphs via mini-batching with disjoint graph representation. (pyg, messagepassing, gnn, gcn, gat, edge_index, knn_graph, global_mean_pool)

原文の言語: 英語

pytorch-ml-training

PyTorch training opinions, pitfalls, and non-obvious patterns. Covers distributed training (DDP/FSDP), optimizer configuration, gradient accumulation, schedulers, and flash attention. Use when scaling training, debugging distributed setups, or making…

原文の言語: 英語

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, dynamic_axes, constant-folding, edge-deployment)

原文の言語: 英語