majiayu000/claude-skill-registry - 32ページ

dynamic-sufficiency

Causal state gating via ε-machine. Coworld observer that prevents action

原文の言語: 英語

east-py-datascience

Data science and machine learning platform functions for the East language (TypeScript types). Use when writing East programs that need optimization (MADS, Optuna, SimAnneal, Scipy), machine learning (XGBoost, LightGBM, NGBoost, Torch MLP, Lightning, GP), ML…

原文の言語: 英語

edge-and-mobile-ml

Use when deploying ML models to edge devices, mobile, or browser. Covers ONNX export, CoreML conversion, TensorRT optimization, quantization (PTQ/QAT), and model profiling.

原文の言語: 英語

edge-model-compression

Edge Model Compression enables deployment of large, accurate machine learning models on resource-constrained edge devices through techniques like quantization, pruning, knowledge distillation, and neu

原文の言語: 英語

embedding

Standalone embedding service for semantic search. Runs as persistent FastAPI server for millisecond-latency embeddings. Supports model swapping via env vars. Use when you need vectors for any database (ArangoDB, Pinecone, etc).

原文の言語: 英語

embedding-strategies

Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.

原文の言語: 英語

embedding-strategy

PROTECTED - Chunking strategy and embedding dimension management

原文の言語: 英語

embeddings

Text embeddings for semantic search and similarity. Use when converting text to vectors, choosing embedding models, implementing chunking strategies, or building document similarity features.

原文の言語: 英語

engineering-features-for-machine-learning

Create, encode, transform, and select features before model fitting. Use when the user needs feature engineering decisions or implementation, not final training ownership or leakage auditing.

原文の言語: 英語

enzyme-autodiff

Enzyme.jl Automatic Differentiation Skill

原文の言語: 英語

esm

ESM2 protein language model for embeddings and sequence scoring. Use this skill when: (1) Computing pseudo-log-likelihood (PLL) scores, (2) Getting protein embeddings for clustering, (3) Filtering designs by sequence plausibility, (4) Zero-shot variant effect…

原文の言語: 英語

esm

Toolkit for protein language models (ESM3 for multimodal generative protein design; ESM C for efficient embeddings). Use when you need sequence/structure/function generation or prediction, inverse folding, protein embeddings, or scalable inference via local…

原文の言語: 英語

eval-and-benchmarking

LLM and ML model evaluation with lm-evaluation-harness, HELM, and custom benchmarks. Covers metric selection, contamination detection, statistical significance, and leaderboard methodology.

原文の言語: 英語

evaluate-model

Measure model performance on test datasets. Use when assessing accuracy, precision, recall, and other metrics.

原文の言語: 英語

evaluating-machine-learning-models

Evaluate trained machine learning models with the right metrics and comparison logic. Use for benchmark review, threshold selection, calibration, validation, and model comparison; not for feature engineering or leakage auditing.

原文の言語: 英語

event-detection-temporal-intelligence-expert

Expert in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event…

原文の言語: 英語

examensvorbereitung-fragen

Examensvorbereitungs-Fragen für 1. und 2. Staatsexamen erstellen: Anwendungsfall Student will Examenswissen durch gezielte Uebungsfragen trainieren und Schwachstellen erkennen. 1. StEx und 2. StEx, JAG Bundesland Bayern NRW Hamburg, Subsumtion Gutachtenstil.…

原文の言語: ドイツ語

experiment-configuration-with-hydra-yaml

Recommends using Hydra or YAML for experiment configuration to ensure clarity and reproducibility.

原文の言語: 英語

experiment-tracker

Manages ML experiment tracking with MLflow, Weights & Biases, or SpecWeave's built-in tracking. Activates for "track experiments", "MLflow", "wandb", "experiment logging", "compare experiments", "hyperparameter tracking". Automatically configures tracking…

原文の言語: 英語

explainable-ai

Make AI model decisions interpretable and transparent. Use for: implementing SHAP for feature importance analysis, using LIME for local explanations, creating attention visualizations for deep learning, generating counterfactual explanations, building…

原文の言語: 英語

extract-hyperparameters

Identify and document model hyperparameters from papers. Use when setting up training configurations.

原文の言語: 英語

faion-embeddings-skill

""

原文の言語: 英語

faion-finetuning-skill

""

原文の言語: 英語

faion-ml-engineer

ML Engineer role: LLM APIs (OpenAI, Claude, Gemini), embeddings, RAG pipelines, fine-tuning, LangChain, LlamaIndex, vector databases (Pinecone, Chroma, Weaviate), prompt engineering, model evaluation, cost optimization.

原文の言語: 英語

faion-ml-ops

ML operations: fine-tuning (LoRA, QLoRA), model evaluation, cost optimization, observability.

原文の言語: 英語

faion-multimodal-ai

Multimodal AI: vision, image/video generation, speech-to-text, text-to-speech, voice synthesis.

原文の言語: 英語

faion-rag-engineer

RAG engineering: embeddings, chunking, vector databases, hybrid search, reranking.

原文の言語: 英語

faion-vector-db-skill

""

原文の言語: 英語

faion-video-gen-skill

""

原文の言語: 英語

fal-image-edit

AI-powered image editing with style transfer and object removal

原文の言語: 英語

fal

Generate images, videos, audio, and more using fal.ai AI models. Use when user requests: "generate image", "create video", "make a picture", "text to image", "image to video", "text to speech", "transcribe audio", "edit image", "remove background", "upscale…

原文の言語: 英語

bio-fastq-quality

Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.

原文の言語: 英語

bio-workflows-fastq-to-variants

End-to-end DNA sequencing workflow from FASTQ files to variant calls. Covers QC, alignment with BWA, BAM processing, and variant calling with bcftools or GATK HaplotypeCaller. Use when calling variants from raw sequencing reads.

原文の言語: 英語

bio-workflows-fastq-to-variants

End-to-end DNA sequencing workflow from FASTQ files to variant calls. Covers QC, alignment with BWA, BAM processing, and variant calling with bcftools or GATK HaplotypeCaller.

原文の言語: 英語

feature-engineer

Comprehensive feature engineering for ML pipelines: data quality assessment, feature creation, selection, transformation, and encoding. Activates for "feature engineering", "create features", "feature selection", "data preprocessing", "handle missing values",…

原文の言語: 英語

feature-store-design

Online/offline feature serving, point-in-time correctness, Feast patterns, and feature computation design.

原文の言語: 英語

bio-rna-quantification-featurecounts-counting

Count reads per gene from aligned BAM files using Subread featureCounts. Use when you have BAM files from STAR/HISAT2 and need gene-level counts for DESeq2/edgeR.

原文の言語: 英語

federated-learning

Train models across distributed clients with privacy-preserving federated algorithms

原文の言語: 英語

fetch-arxiv-papers

Fetch recent AI/ML research papers from arXiv RSS feeds and store them in memory. Uses RSS tool for fetching and memory MCP for storage and deduplication.

原文の言語: 英語

fibonacci-optimization

Optimización evolutiva y paramétrica basada en Fibonacci y el Número Áureo (phi).

原文の言語: スペイン語