Skill UI

Phoenix is an open-source observability platform for tracing, evaluating, and monitoring LLM applications; use it to debug prompts, run dataset evaluations, build experiment pipelines, and watch production inference in real time.

A comprehensive guide for integrating Plaid API into fintech applications. Covers secure link token creation, public token exchange for persistent access tokens, and real-time transaction synchronization using the /transactions/sync endpoint. Includes best practices for identity verification, ACH authentication, and webhook handling, ensuring robust financial data connectivity.

Use Azure OpenAI Realtime Mini to turn text prompts into streamed PCM audio, convert it to WAV, and deliver base64 payloads for frontend playback, handling transcripts and voice tuning for podcast-style narration.

This guide provides comprehensive strategies for implementing privacy-safe analytics using PostHog. It addresses critical compliance requirements like GDPR and CCPA, covering explicit consent management (opt-in/opt-out), real-time property sanitization (stripping PII like IP or tokens), and methods for handling Data Subject Access Requests (SAR) and the Right to Erasure. Use this to build highly compliant and privacy-preserving analytics pipelines.

This guide provides a comprehensive workflow for setting up a robust local development environment for PostHog integrations. It covers enabling debug mode for real-time event inspection, implementing mocking strategies for stable unit testing, and configuring integration tests using a dedicated development PostHog project. Use this when building or testing analytics tracking features with posthog-js or posthog-node to ensure fast, isolated development cycles.

This skill guides you through integrating PostHog's Customer Data Platform (CDP) features. It covers setting up webhooks to trigger real-time actions (e.g., syncing to CRM, sending notifications) when specific user events occur. Furthermore, it demonstrates how to query event data using the Events API and perform complex funnel analysis using HogQL, allowing for deep, custom insights into user behavior.

Qdrant is a high-performance, Rust-powered vector database designed for production-grade RAG (Retrieval-Augmented Generation) and semantic search applications. It provides fast nearest neighbor search, supports complex hybrid search using metadata filtering, and offers horizontal scalability through sharding and replication. Ideal for building real-time recommendation systems and enterprise-level knowledge retrieval.

Specializes in building modern, high-performance Rails 7+ web applications. Expertise includes optimizing Active Record queries (N+1 prevention), implementing partial page updates with Hotwire (Turbo Frames/Streams), handling real-time communication via Action Cable, and managing background jobs using Sidekiq. The process includes rigorous RSpec testing and database schema management.

This skill provides implementation patterns for cost tuning within the Retell AI platform, specifically tailored for voice agents and complex telephony workflows. It helps developers build, monitor, and optimize the operational costs of AI-powered voice automation systems, ensuring efficient resource management when integrating real-time voice services.

This skill provides implementation patterns for developing local voice agents and automating phone calls using the Retell AI SDK. It guides developers through the necessary steps for integrating complex real-time voice interactions, telephony platforms, and building automated customer service agents, ensuring robust development and error handling practices.

Provides implementation patterns and reference architecture for building advanced AI voice agents and automating complex phone call workflows using the Retell AI SDK. This skill is designed for developers requiring robust voice interaction, real-time telephony integration, and comprehensive conversational AI capabilities in their applications.

This skill provides a comprehensive guide for setting up and managing webhook endpoints for Retell AI. It allows developers to capture and process crucial call lifecycle events—such as call start, end, and analysis—as well as handle function calls triggered during live conversations. Use this when building sophisticated voice agents or call automation systems that require real-time backend interaction with Retell AI.