Skill UI

Manages and enforces project-specific coding standards and architectural conventions within the Cursor IDE. Developers can define rules using `.mdc` files, specifying required patterns (e.g., TypeScript strict mode, React component structure, API validation). This system guides the AI assistant by providing deep context, ensuring code consistency and adherence to best practices across the entire codebase.

A comprehensive guide for diagnosing and fixing common integration errors with Customer.io. It covers critical topics such as API status codes (400, 401, 429), authentication failures, incorrect timestamp formatting, and best practices for event tracking and transactional message delivery. Use this resource when troubleshooting campaign failures or API calls failing.

This comprehensive guide details how to install and configure the Customer.io SDK for programmatic integration in Node.js projects. It covers the critical setup of authentication using two distinct API keys: the Track API Key (for user identification and event tracking) and the App API Key (for sending transactional messages and broadcasts). Essential for developers integrating Customer.io's core customer data and marketing features.

This comprehensive guide identifies and explains the most common anti-patterns and mistakes when integrating with Customer.io. It covers crucial development topics, including proper API key usage, Unix timestamp formatting, ensuring correct event tracking order (Identify before Track), and optimizing API calls for performance. Use this as a definitive checklist for code review and developer onboarding.

This guide provides comprehensive strategies for scaling Customer.io integrations to handle high volumes of daily events. It covers implementing k6 load tests for performance benchmarking and outlines architectural patterns—from simple Direct APIs to complex Redis/Kafka queue-backed systems—ensuring reliability and managing API rate limits for massive data throughput.

This comprehensive guide details essential security best practices for integrating with Customer.io. It covers secure credential storage using secrets managers, sanitizing Personally Identifiable Information (PII) via hashing, verifying webhook signatures (HMAC-SHA256) to ensure data integrity, and establishing procedures for API key rotation to maintain compliance with GDPR/CCPA regulations.

A comprehensive guide for safely upgrading and migrating the Customer.io Node SDK. It details the necessary steps for handling major version changes, such as transitioning from the legacy CustomerIO class to the modern TrackClient and APIClient pattern. Use this skill when refactoring old code, adapting to breaking API changes, or ensuring compatibility with the latest SDK best practices.

A comprehensive guide and implementation pattern for managing rate limits, throttling, and ensuring idempotency when interacting with the Databricks API. This skill demonstrates techniques like exponential backoff with jitter, token-bucket rate limiting, and using idempotency tokens to make bulk and concurrent API calls reliable and efficient, minimizing HTTP 429 errors.

This comprehensive guide sets up a robust CI/CD pipeline for Deepgram integrations using GitHub Actions. It covers unit tests (mocked SDK), full integration tests against the live Deepgram API (including transcription, diarization, and TTS), and smoke tests. Use this when establishing automated testing, ensuring deployment stability, or implementing continuous delivery workflows for Deepgram-powered applications.

A comprehensive guide for diagnosing and fixing common Deepgram API errors. Covers HTTP error codes, WebSocket issues, optimal audio preparation using ffmpeg, and implementing robust retry patterns for reliable Speech-to-Text integration.

This guide provides minimal working examples for Deepgram speech-to-text transcription. It demonstrates how to transcribe audio from a URL or a local file using both TypeScript and Python. Users can learn basic API patterns, implement advanced features like diarization (speaker identification), and compare various model options (e.g., nova-3, nova-2). Ideal for initial integration and testing.

This guide establishes a robust local development environment for Deepgram integrations. It covers setting up test fixtures using sample audio, mocking API responses for isolated unit testing, configuring watch-mode development servers, and running comprehensive unit and integration tests using Vitest. Use this setup when initiating a Deepgram feature or requiring a reliable, fast development cycle.