Skill UI

This guide provides comprehensive instructions for setting up robust CI/CD pipelines for Instantly.ai integrations using GitHub Actions. It covers unit and integration testing against both a mock server and the live API, includes API scope validation scripts, and details the deployment process for webhook receivers (e.g., to Cloud Run). Use this when ensuring continuous validation and reliable deployment of your Instantly API code.

This skill guide provides comprehensive instructions for deploying Instantly.ai's API v2 webhook receivers and automation services to major cloud platforms. It covers setting up resilient, public HTTPS endpoints using Vercel serverless functions, Google Cloud Run containers, or Fly.io services. Use this when moving from local development to production or setting up robust webhook endpoints that handle real-time event processing.

This comprehensive guide enables developers to set up a robust local development environment for Instantly API integrations. It utilizes a dedicated mock server to allow for safe testing of API calls, writing comprehensive integration tests, and simulating webhook events without consuming real credentials or exceeding rate limits. Ideal for building reliable SaaS connectors.

A comprehensive reference architecture guide providing the best-practice project layout and implementation structure for building scalable outreach automation platforms using the Instantly API v2. This blueprint covers core modules including API client wrappers, campaign lifecycle management, lead enrichment pipelines, event-driven webhook processing, and analytics synchronization, ensuring a robust and maintainable system.

A comprehensive guide detailing security best practices for integrating with Instantly.ai. Learn how to implement least-privilege API scopes (e.g., campaigns:read), manage secrets using environment variables or dedicated secret managers, execute secure API key rotations, and validate incoming webhooks using custom headers. This skill is essential for developers building robust, secure, and scalable SaaS integrations.

Guides the implementation and handling of Instantly.ai API v2 webhooks. Users can process real-time events, such as email opens, link clicks, replies, bounces, and lead status changes. This is essential for building robust CRM synchronization pipelines and automating marketing workflows based on actual outreach activity.

Automates guidance for API integration testing by activating whenever integration test generator topics arise, offering patterns, best practices, and production-ready code plus validation for webhooks, SDKs, OAuth, and third-party integrations.

Specialized skill for designing, building, and optimizing modern, cloud-native enterprise Java applications. Covers microservices architecture, Spring Boot 3.x, reactive programming (WebFlux), advanced data persistence (JPA optimization, R2DBC), and robust security implementation (OAuth2/JWT). Use this when implementing DDD patterns, ensuring high test coverage, and managing complex transaction boundaries.

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.

This skill provides the framework for connecting to and handling Juicebox webhooks and real-time events. It allows developers to build automated pipelines that react instantly to key events—such as analysis completion, dataset updates, and export readiness—without constantly polling the API. Implementation includes signature verification and robust event routing logic for reliable data processing.

A comprehensive guide and expert resource for mastering Julia 1.10+ development. Covers advanced topics including multiple dispatch, performance optimization, type stability, and modern tooling. Ideal for building production-ready applications in scientific computing, machine learning, data science, and web development.

This tool provides comprehensive Python solutions for processing batches of text-to-video requests using the Kling AI API. It handles controlled parallelism, rate-limiting, and detailed status tracking. Use this when building robust content pipelines that require generating multiple videos efficiently from a list of prompts, supporting synchronous, asynchronous, and webhook callback methods.