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DevOps & Cloud
Deployment, cloud, containers, CI/CD, monitoring, and infrastructure
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Showing 8,881–8,904 of 20,326 skills
- Video DownloaderDownload YouTube videos with customizable quality and format options. Use this skill when the user asks to download, save, or grab YouTube videos. Supports various quality settings (best, 1080p, 720p, 480p, 360p), multiple formats (mp4, webm, mkv), and audio-only downloads as MP3.Votes: 0GitHub stars: 11
- Quant AnalystUse this agent when you need to develop quantitative trading strategies, build financial models with rigorous mathematical foundations, or conduct advanced risk analytics for derivatives and portfo...Votes: 0GitHub stars: 11
- Legacy ModernizerUse this agent when modernizing legacy systems that need incremental migration strategies, technical debt reduction, and risk mitigation while maintaining business continuity.Votes: 0GitHub stars: 11
- Gemini String ReviewerUse this skill when asked to review text and user-facing strings within the codebase. It ensures that these strings follow rules on clarity, usefulness, brevity and style.Votes: 0GitHub stars: 11
- Dx OptimizerUse this agent when optimizing the complete developer workflow including build times, feedback loops, testing efficiency, and developer satisfaction metrics across the entire development environment.Votes: 0GitHub stars: 11
- Build EngineerUse this agent when you need to optimize build performance, reduce compilation times, or scale build systems across growing teams.Votes: 0GitHub stars: 11
- Fintech EngineerUse when building payment systems, financial integrations, or compliance-heavy financial applications that require secure transaction processing, regulatory adherence, and high transaction accuracy.Votes: 0GitHub stars: 11
- Mcp DeveloperUse this agent when you need to build, debug, or optimize Model Context Protocol (MCP) servers and clients that connect AI systems to external tools and data sources.Votes: 0GitHub stars: 11
- Iot EngineerUse when designing and deploying IoT solutions requiring expertise in device management, edge computing, cloud integration, and handling challenges like massive device scale, complex connectivity s...Votes: 0GitHub stars: 11
- Postgres ProUse when you need to optimize PostgreSQL performance, design high-availability replication, or troubleshoot database issues at scale. Invoke this agent for query optimization, configuration tuning,...Votes: 0GitHub stars: 11
- Data EngineerUse this agent when you need to design, build, or optimize data pipelines, ETL/ELT processes, and data infrastructure. Invoke when designing data platforms, implementing pipeline orchestration, han...Votes: 0GitHub stars: 11
- Ai EngineerUse this agent when architecting, implementing, or optimizing end-to-end AI systems—from model selection and training pipelines to production deployment and monitoring.Votes: 0GitHub stars: 11
- Hf Hugging Face Vision TrainerTrains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation,...Votes: 0GitHub stars: 11
- Hf Hugging Face Model TrainerThis skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked f...Votes: 0GitHub stars: 11
- Hf Hugging Face JobsThis skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention ...Votes: 0GitHub stars: 11
- Data Engineering ExpertExpert-level data engineering. Use when building data pipelines, ETL/ELT processes, working with Apache Spark, Airflow, dbt, data warehouses (Snowflake, BigQuery, Redshift), data lakes, or streaming pipelines. Also use when the user mentions 'data pipeline', 'ETL', 'ELT', 'dbt', 'Airflow', 'Spark', 'data warehouse', 'data lake', 'streaming', 'partitioning', or 'data quality'.Votes: 0GitHub stars: 11
- Mlops ExpertExpert-level MLOps and ML infrastructure. Use when setting up ML pipelines, model registries (MLflow, W&B), model serving (Triton, BentoML), A/B testing models, data versioning (DVC), feature stores, or monitoring ML models in production. Also use when the user mentions 'MLflow', 'model registry', 'model serving', 'feature store', 'concept drift', 'data drift', 'model monitoring', 'DVC', or 'ML pipeline'.Votes: 0GitHub stars: 11
- Mlops EngineerUse this agent when you need to design and implement ML infrastructure, set up CI/CD for machine learning models, establish model versioning systems, or optimize ML platforms for reliability and au...Votes: 0GitHub stars: 11
- VllmServes LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.Votes: 0GitHub stars: 11
- Tensorrt LlmOptimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.Votes: 0GitHub stars: 11
- Deep Learning ExpertExpert-level deep learning with PyTorch and TensorFlow. Use when building neural networks, CNNs, RNNs, transformers, training loops, loss functions, backpropagation, GPU optimization, or fine-tuning pretrained models. Also use when the user mentions 'neural network', 'PyTorch', 'transformer', 'fine-tuning', 'backpropagation', 'GPU training', 'loss function', 'overfitting', 'batch normalization', or 'transfer learning'.Votes: 0GitHub stars: 11
- Ml EngineerUse this agent when building production ML systems requiring model training pipelines, model serving infrastructure, performance optimization, and automated retraining.Votes: 0GitHub stars: 11
- Machine Learning EngineerUse this agent when you need to deploy, optimize, or serve machine learning models at scale in production environments.Votes: 0GitHub stars: 11
- Microservices ExpertExpert-level microservices architecture. Use when designing microservices, service boundaries, inter-service communication, saga pattern, CQRS, event sourcing, service mesh, API gateways, or managing distributed systems complexity. Also use when the user mentions 'microservices', 'service boundary', 'saga pattern', 'service mesh', 'CQRS', 'event sourcing', 'API gateway', 'distributed transaction', or 'service decomposition'.Votes: 0GitHub stars: 11