Skill UI

Automates JMeter test plan creation and validation for load, stress, and benchmarking scenarios; triggers whenever you request the jmeter test plan creator and delivers production-ready configs aligned with best practices.

Auto-activating tool that guides technical documentation work by providing jsdoc comment templates, best practices, and validation for APIs, guides, and automation workflows.

Automates json config manager workflows in DevOps basics by offering guidance, industry best practices, production-ready configs, and validation across version control, containerization, CI/CD, and infrastructure fundamentals.

This comprehensive guide addresses common technical and business logic errors encountered when integrating with the Juicebox API. It covers HTTP status codes (e.g., 401, 403, 429), including authentication failures, quota exhaustion, rate limiting, data validation issues, and analysis timeouts. The resource provides detailed causes, specific fixes, and best practices for building reliable and robust integrations into recruiting and research workflows.

This comprehensive checklist guides the operational validation of the Juicebox AI talent search and analysis platform in a production environment. It ensures system reliability, data security, and service continuity by reviewing critical areas such as API key management, rate limit handling, robust error detection (circuit breakers, exponential backoff), data encryption (GDPR/CCPA compliance), and comprehensive monitoring setup. It is essential for preventing service failures and maintaining search data integrity.

This guide provides comprehensive security best practices for integrating with the Juicebox API. It covers critical areas such as secure API key management (using secrets managers), robust webhook signature verification, input validation using schemas, and essential data protection techniques like PII redaction. It ensures compliance with global regulations like GDPR and CCPA when handling sensitive professional and contact data.

Auto-activating helper that provides step-by-step guidance, best practices, and validation for generating production-ready k6 load test scripts, configs, and benchmarking workflows.

Automates Kafka stream processor workflows within data pipelines, offering step-by-step guidance, best practices, production-ready code and configurations, and validation to support ETL, data transformation, workflow orchestration, and streaming data processing.

Guides frontend developers through keyboard navigation testing, offering best-practice advice, code snippets, and automated validation for accessibility, frameworks, and performance.

Automates KPI dashboard template tasks within enterprise workflows by offering guidance, best-practice patterns, production-ready code/configuration, and validation for compliance, governance, and integration scenarios.

Automates KPI definition tasks for data analytics teams, offering best-practice guidance, code templates, and validation to streamline SQL, visualization, and BI workflows.

Auto-activating DevOps skill that guides Kubernetes deployment creation with best practices, production-ready IaC configurations, and validation across Terraform, Helm, and monitoring workflows.