Explore our collection of Agent Skills to enhance your AI workflow.
Measures test suite quality by introducing code mutations and identifying gaps in logic coverage.
Identifies SQL injection vulnerabilities in your codebase and provides actionable remediation guidance to secure your database interactions.
Automates the deployment and configuration of centralized logging systems like ELK, Loki, and Splunk for production environments.
Automates the end-to-end creation of machine learning pipelines, including feature engineering, model selection, and hyperparameter tuning.
Generates production-ready Kubernetes manifests including deployments, services, and ingress configurations following industry best practices.
Analyzes network traffic patterns and optimizes request handling to reduce latency and improve application performance.
Implements comprehensive database audit logging and change tracking to ensure data integrity and regulatory compliance.
Analyzes HTTP security headers to identify vulnerabilities and provide actionable recommendations for website hardening.
Analyzes HTTP security headers to identify vulnerabilities and provides actionable remediation recommendations for website hardening.
Tracks and executes regression tests to ensure code stability and prevent functional regressions during development.
Optimizes SQL queries and database performance by identifying bottlenecks, suggesting indexes, and rewriting complex queries.
Performs comprehensive security audits and vulnerability assessments for PostgreSQL and MySQL databases using OWASP standards.
Scans your codebase for exposed credentials, API keys, and private keys to prevent security breaches and accidental leaks.
Enhances test suite quality by executing mutation testing to identify logic gaps and measure true test effectiveness.
Generates mocks, stubs, and spies for unit tests by automatically analyzing code dependencies and supporting popular testing frameworks.
Audits web application codebases to identify and remediate session management vulnerabilities like fixation and insecure IDs.
Optimizes machine learning models by automatically searching for the best hyperparameter configurations using advanced search strategies.
Automates autonomous software development through Git hook-enforced Test-Driven Development (TDD).
Identifies statistical outliers and data irregularities using machine learning algorithms to uncover fraud, security threats, or system errors.
Automates PostgreSQL backup management and disaster recovery using pgBackRest and Wasabi S3 storage.
Manages and updates snapshot tests across popular JavaScript frameworks using intelligent diff analysis to distinguish regressions from intentional UI changes.
Analyzes and optimizes application network request patterns to reduce latency and improve communication efficiency.
Analyzes application log files to identify performance bottlenecks, recurring error patterns, and resource usage anomalies.
Scans codebases for exposed secrets, API keys, and credentials to prevent security vulnerabilities before deployment.
Trains, evaluates, and persists machine learning models using automated workflows for classification and regression tasks.
Analyzes cloud infrastructure configurations to ensure alignment with SOC2, HIPAA, and PCI-DSS industry standards.
Evaluates machine learning model performance using comprehensive metrics like accuracy, precision, and F1-score to ensure model quality.
Automates the configuration of uptime, transaction, and API monitoring to proactively track application performance and availability.
Automates the end-to-end creation, training, and evaluation of machine learning classification models within Claude Code.
Scans codebases and infrastructure configurations to identify potential HIPAA compliance violations and security vulnerabilities.
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