Explore our collection of Agent Skills to enhance your AI workflow.
Implements production-grade safety patterns and robust error handling in shell scripts for reliable automation and system utilities.
Simplifies the creation of custom slash commands for Claude Code using official implementation patterns.
Facilitates the creation, structuring, and distribution of production-grade Python packages using modern standards like pyproject.toml and PyPI.
Implements robust end-to-end testing architectures using Playwright and Cypress to ensure application reliability and prevent regressions.
Generates production-ready FastAPI applications with standardized architecture, async patterns, and dependency injection.
Executes autonomous multi-step research tasks across genomics, drug discovery, and clinical analysis using integrated biomedical databases.
Configures secure, high-performance connectivity between on-premises infrastructure and cloud platforms using VPN and dedicated connections.
Builds and optimizes high-performance GitLab CI/CD pipelines using standardized patterns for testing, deployment, and infrastructure.
Masters systematic debugging techniques and root cause analysis to identify and resolve complex software bugs across any technology stack.
Generates structured summaries and analyses of git activity for code reviews, retrospectives, and session documentation.
Implements secure handling, storage, and rotation of sensitive credentials across major CI/CD platforms and cloud providers.
Automates complex biomedical research tasks including genomics, drug discovery, and clinical data analysis using an autonomous agent framework.
Guides the development of high-performance web services and APIs using the Rust ecosystem.
Master the foundational syntax and precision parameterization required for BUGS and JAGS statistical modeling.
Executes database schema and data migrations across multiple ORMs with zero-downtime strategies and rollback procedures.
Provides foundational knowledge for writing, reviewing, and optimizing high-performance Stan 2.37 Bayesian models.
Optimizes cloud infrastructure spending through resource rightsizing, reserved instance strategies, and automated cost governance.
Refactors legacy React codebases to modern standards including Hooks, React 18 concurrent features, and TypeScript.
Minimizes context window consumption by automatically suppressing verbose success outputs from development commands while preserving critical error logs.
Design secure, multi-stage CI/CD pipelines with manual approval gates, automated rollbacks, and advanced deployment orchestration.
Enforces a synthesis-first memory system to capture and retrieve critical decisions and learnings across development sessions.
Implements advanced Bayesian time series analysis using Stan and JAGS for probabilistic forecasting and state-space modeling.
Scaffolds production-ready FastAPI applications with async patterns, dependency injection, and clean architectural layers.
Profiles and optimizes Python code to eliminate bottlenecks, reduce memory usage, and improve execution speed.
Implements and optimizes hierarchical Bayesian models with support for partial pooling and advanced parameterization techniques.
Implement defense-in-depth Kubernetes security through network policies, RBAC configurations, and pod security standards.
Generates production-ready GitHub Actions workflows for automated testing, building, and multi-environment deployment.
Evaluates Bayesian model convergence and sampling performance using MCMC diagnostics for Stan and JAGS frameworks.
Implements PCI DSS requirements to secure payment card data and maintain industry-standard payment processing security.
Validates KrakenD gateway configurations for syntax errors, edition compatibility, and architectural anti-patterns.
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