All categories
DevOps & Cloud
Deployment, cloud, containers, CI/CD, monitoring, and infrastructure
- 19,579
- 816
Security grades appear on each card once the skill has been scanned. Newly imported skills may briefly show without a grade until the backfill job runs.
Open in full browserBrowse devops & cloud skills
Showing 15,313–15,336 of 19,579 skills
- Powershell MasterComplete PowerShell expertise system across ALL platforms (Windows/Linux/macOS). PROACTIVELY activate for: (1) ANY PowerShell task (scripts/modules/cmdlets), (2) CI/CD automation (GitHub Actions/Azure DevOps/Bitbucket), (3) Cross-platform scripting, (4) Module discovery and management (PSGallery), (5) Azure/AWS/Microsoft 365 automation, (6) Script debugging and optimization, (7) Best practices and security. Provides: PowerShell 7+ features, popular module expertise (Az, Microsoft.Graph, PnP, ...Votes: 0GitHub stars: 666
- Firewall Appliance· Manage OPNsense/pfSense via SSH: pfctl, pf rules, CARP, CrowdSec, pfBlockerNG. Triggers: 'opnsense', 'pfsense', 'pfctl', 'CARP', 'configctl'. Not for Linux firewalls.Votes: 0GitHub stars: 666
- Defensive BashProduction-grade defensive Bash scripting for server automation, monitoring, and DevOps tasks. Emphasizes safety, error handling, idempotency, and logging.Votes: 0GitHub stars: 666
- Command Prompt· Write/debug shell commands, scripts, dotfiles, completions for zsh, bash, POSIX sh, fish. Triggers: 'shell', 'script', '.zshrc', '.bashrc', 'alias', 'completion', 'trap'. Not for CI blocks (use ci-cd).Votes: 0GitHub stars: 666
- Triage Jordangunn SkillsPerform breadth-first hypothesis surfacing and prioritization across all ownership zones, without commitment. This is not diagnosis and not investigation.Votes: 0GitHub stars: 666
- Touch SweepFinds every file and location affected by a GitHub issue change. Use when scoping an issue, finding blast radius, or answering "what does this touch". Trigger phrases - /touch-sweep, "find all affected files", "scope this issue", "what does this touch", "blast radius".Votes: 0GitHub stars: 666
- Search Company KnowledgeSearch across company knowledge bases (Confluence, Jira, internal docs) to find and explain internal concepts, processes, and technical details. When Claude needs to: (1) Find or search for information about systems, terminology, processes, deployment, authentication, infrastructure, architecture, or technical concepts, (2) Search internal documentation, knowledge base, company docs, or our docs, (3) Explain what something is, how it works, or look up information, or (4) Synthesize informatio...Votes: 0GitHub stars: 666
- Review HealthFirst-pass strategic-orientation review of a repository. Produces an evidence-cited map (not a grade) calibrated to a reference class, helping the user decide where to engage, where to tread carefully, and where to leave alone. Advisory only — no changes made.Votes: 0GitHub stars: 666
- Python Architecture Review Rknall Claude Skills 2Comprehensive design architecture review for Python backend applications. Use this skill when users ask you to review, analyze, or provide feedback on backend architecture designs, system design documents, or Python application architecture. Covers scalability, security, performance, database design, API design, microservices patterns, deployment architecture, and best practices.Votes: 0GitHub stars: 666
- Pattern Extraction Lobbi Docs Claude 2Detect and extract patterns from codebases for template generationVotes: 0GitHub stars: 666
- Architecture Review Ionfury HomelabArchitecture evaluation criteria and technology standards for the homelab. Preloaded into the designer agent to ground design decisions in established patterns and principles. Use when: (1) Evaluating a proposed technology addition, (2) Reviewing architecture decisions, (3) Assessing stack fit for a new component, (4) Comparing implementation approaches. Triggers: "architecture review", "evaluate technology", "stack fit", "should we use", "technology comparison", "design review", "architect...Votes: 0GitHub stars: 666
- Arch Lens OperationalCreate Operational architecture diagram showing CLI workflows, configuration, and observability. Administration lens answering "How is it run and monitored?"Votes: 0GitHub stars: 666
- Arch Lens Operational Trecek Useful Claude SkillsCreate Operational architecture diagram showing CLI workflows, configuration, and observability. Administration lens answering "How is it run and monitored?"Votes: 0GitHub stars: 666
- When Training Neural Networks Use Flow Nexus Neural Dnyoussef Ai Dnyoussef Ai Chrome Extensionskillname: when-training-neural-networks-use-flow-nexus-neuralVotes: 0GitHub stars: 666
- Verify Training Pipeline Kungfuai CvlizationVerify a CVlization training pipeline example is properly structured, can build, trains successfully, and logs appropriate metrics. Use when validating example implementations or debugging training issues.Votes: 0GitHub stars: 666
- Using Training Optimization Tachyon Beep Skillpacks 2Router to training optimization skills based on symptoms and training problemsVotes: 0GitHub stars: 666
- Using Ml ProductionRouter skill directing to deployment, optimization, MLOps, and monitoring guides.Votes: 0GitHub stars: 666
- Two SigmaBuild trading systems in the style of Two Sigma, the systematic investment manager pioneering machine learning at scale. Emphasizes alternative data, distributed computing, feature engineering, and rigorous ML infrastructure. Use when building ML pipelines for alpha research, feature stores, or large-scale backtesting systems.Votes: 0GitHub stars: 666
- Senior Ml EngineerWorld-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.Votes: 0GitHub stars: 666
- Senior Ml Engineer Hainamchung Agent AssistantWorld-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.Votes: 0GitHub stars: 666
- Senior Data ScientistWorld-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.Votes: 0GitHub stars: 666
- Senior Data Scientist Eyh0602 SkillshubWorld-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.Votes: 0GitHub stars: 666
- Pipeline Atacseq Ammawla Encode ToolkitExecute ENCODE ATAC-seq processing pipeline from FASTQ to peaks and signal tracks. Child of pipeline-guide. Provides stage-by-stage Nextflow execution with Docker containers and cloud deployment. Handles Tn5 transposase offset correction, mitochondrial read removal, nucleosome-free fragment selection, and TSS enrichment scoring. Use when users need to process ATAC-seq data following ENCODE standards. Trigger on: ATAC-seq pipeline, run ATAC-seq, process ATAC-seq, chromatin accessibility, open ...Votes: 0GitHub stars: 666
- Model DeploymentDeploy trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms. Use when the user requests model deployment or provides relevant inputs for this workflow.Votes: 0GitHub stars: 666