Explore our collection of Agent Skills to enhance your AI workflow.
Analyzes code coverage metrics to identify untested code paths and generate comprehensive reports for improved software quality.
Analyzes and optimizes SQL queries to improve database performance through indexing suggestions and structural rewrites.
Scans codebases and infrastructure configurations to identify potential HIPAA compliance violations and security vulnerabilities.
Automates the configuration of proactive performance tracking, uptime checks, and API monitoring for web applications.
Automates autonomous software development through Git hook-enforced Test-Driven Development (TDD).
Generates comprehensive database documentation, including ERD diagrams and data dictionaries, from existing schemas.
Generates realistic, schema-compliant test data including users, products, and complex business objects for software testing and development.
Automates mobile application testing across iOS and Android platforms using industry-standard frameworks like Appium, Detox, and XCUITest.
Automates the creation and execution of end-to-end mobile tests for iOS and Android applications using industry-standard frameworks.
Automates the end-to-end machine learning workflow from dataset analysis and model selection to training and artifact persistence.
Automates the creation of scheduled, encrypted, and compressed database backups for major SQL and NoSQL systems.
Automates end-to-end software development sessions using Git hooks to enforce rigorous test-driven development (TDD) workflows.
Audits codebases, cloud infrastructure, and documentation to identify potential HIPAA compliance violations and security risks.
Monitors database transactions in real-time to detect lock contention, long-running queries, and performance anomalies.
Analyzes cloud infrastructure configurations to ensure alignment with SOC2, HIPAA, and PCI-DSS industry standards.
Identifies and resolves memory leaks, performance bottlenecks, and resource management issues within your codebase.
Automates the partitioning of datasets into training, validation, and testing sets for machine learning development.
Automates the end-to-end creation, training, and evaluation of supervised machine learning classification models.
Automates the restoration of stable application versions and performs safety verification checks during deployment failures.
Automates the end-to-end creation, training, and evaluation of machine learning classification models within Claude Code.
Trains, evaluates, and persists machine learning models using automated workflows for classification and regression tasks.
Forecasts future values and identifies temporal patterns in historical data using advanced statistical modeling.
Configures production-ready service meshes like Istio and Linkerd to automate microservices traffic management, security, and observability.
Analyzes database workloads and query patterns to provide actionable recommendations for optimizing and managing indexes.
Generates realistic, schema-compliant test data for software development, database population, and automated testing workflows.
Analyzes text data to extract sentiment, keywords, and topics using advanced natural language processing techniques.
Generates production-ready CI/CD pipeline configurations for GitHub Actions, GitLab CI, and Jenkins to automate software delivery workflows.
Orchestrates complex test execution graphs with parallel processing and intelligent test selection to optimize software quality cycles.
Tests and validates load balancing strategies, including traffic distribution, failover scenarios, and session persistence.
Automates the creation of production-ready ArgoCD and Flux configurations for Kubernetes deployments.
Scroll for more results...