> browse/registry

> event-store-design

Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.

> managing-environment-configurations

This skill enables Claude to manage environment configurations and secrets across different deployments using the environment-config-manager plugin. It is invoked when the user needs to generate, update, or retrieve configuration settings for various environments (e.g., development, staging, production). Use this skill when the user explicitly mentions "environment configuration," "secrets management," "deployment configuration," or asks to "generate config files". It helps streamline DevOps wor

> database-migrations-migration-observability

Migration monitoring, CDC, and observability infrastructure

> hybrid-cloud-networking

Configure secure, high-performance connectivity between on-premises infrastructure and cloud platforms using VPN and dedicated connections. Use when building hybrid cloud architectures, connecting data centers to cloud, or implementing secure cross-premises networking.

> hexagonal-architecture-layers-java

Hexagonal architecture layering for Java services with strict boundaries. Trigger: When structuring Java apps by Domain/Application/Infrastructure, or refactoring toward clean architecture.

> omnissa-horizon-desktops

Manage, deploy, secure, and operate VMware Horizon desktop fleets (on‑premises or cloud-hosted) with domain-join, image pipelines, automation, and monitoring.

> incident-response-smart-fix

[Extended thinking: This workflow implements a sophisticated debugging and resolution pipeline that leverages AI-assisted debugging tools and observability platforms to systematically diagnose and res

> verl-rl-training

Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.

> machine-learning-ops-ml-pipeline

Design and implement a complete ML pipeline for: $ARGUMENTS

> biopython

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

> mlops-engineer

Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools. Implements automated training, deployment, and monitoring across cloud platforms. Use PROACTIVELY for ML infrastructure, experiment management, or pipeline automation.

> ml-engineer

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring. Use PROACTIVELY for ML model deployment, inference optimization, or production ML infrastructure.

> flutter-security

Security standards for Flutter applications based on OWASP Mobile. Use when applying OWASP Mobile security standards or securing a Flutter application. (triggers: lib/infrastructure/**, pubspec.yaml, secure_storage, obfuscate, jailbreak, pinning, PII, OWASP)

> spark-optimization

Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.

> building-cicd-pipelines

This skill enables Claude to generate CI/CD pipeline configurations for various platforms, including GitHub Actions, GitLab CI, and Jenkins. It is used when a user requests the creation of a CI/CD pipeline, specifies a platform (e.g., "GitHub Actions"), or mentions specific pipeline stages like "test," "build," "security," or "deploy." This skill is also useful when the user needs to automate software delivery, integrate security scanning, or set up multi-environment deployments. The skill is tr

> azure-app-testing

Expert knowledge for Azure App Testing development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building, debugging, or optimizing Azure App Testing applications. Not for Azure Test Plans (use azure-test-plans), Playwright Workspaces (use azure-playwright-workspaces), Azure DevOps (use azure-devops), Azure App Service (use azure-app-service).

> scanpy

Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use anndata.

> secrets-management

Implement secure secrets management for CI/CD pipelines using Vault, AWS Secrets Manager, or native platform solutions. Use when handling sensitive credentials, rotating secrets, or securing CI/CD environments.

> pytorch-lightning

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

> pysam

Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.