Skill UI

This utility provides comprehensive patterns for reliably integrating with the Deepgram API. It implements concurrency-aware rate limiting (using p-limit), exponential backoff with jitter for retries, and a circuit breaker pattern. Use this when building high-volume, mission-critical applications that must handle API quotas, 429 rate limit errors, and temporary service disruptions gracefully.

A comprehensive guide detailing security best practices for Deepgram API integration. It covers critical topics such as implementing scoped API keys, key rotation strategies, enabling built-in PII redaction for sensitive data, generating temporary client-side keys, and validating audio URLs to prevent SSRF attacks. Use this when building robust, production-grade applications requiring high data security and compliance.

This skill provides comprehensive guidance on implementing distributed tracing using industry standards like OpenTelemetry and tools such as Jaeger/Tempo. It enables developers to monitor the end-to-end lifecycle of a request across multiple microservices. Use this skill to debug latency issues, visualize complex service dependencies, pinpoint performance bottlenecks, and accurately trace error propagation in highly distributed systems.

This skill provides patterns for building highly resilient applications that interact with external APIs. It covers crucial concepts like Exponential Backoff with Jitter, request queuing for bulk operations, and the Circuit Breaker pattern. Use this when your application needs to handle rate limit errors (429), transient network failures, or temporary service outages, ensuring reliable throughput and graceful degradation.

Mastery of advanced system design patterns, including Event Sourcing, CQRS, and Event-Driven Architecture (EDA). This skill covers designing event stores, building read/write projections, orchestrating sagas, and managing eventual consistency. It is ideal for building complex microservices that require guaranteed audit trails, historical state querying (temporal queries), and robust handling of business workflows with compensating actions.

This skill addresses the challenge of handling temporary CDN links for videos generated by Kling AI. It provides a comprehensive, multi-cloud solution to download the video asset and persistently upload it to major cloud storage platforms, including AWS S3, Google Cloud Storage (GCS), and Azure Blob Storage. It facilitates building robust, long-term media pipelines and ensures metadata preservation.

A comprehensive guide detailing the foundational principles of modern SEO. It covers critical areas such as E-E-A-T framework, Core Web Vitals, technical SEO implementation (e.g., sitemaps, structured data), and advanced content quality strategies. This skill helps users build sustainable, high-trust online visibility by focusing on user experience and search engine understanding, not temporary hacks.

A comprehensive guide and expert resource for mastering durable workflow orchestration using the Temporal Python SDK. Covers advanced patterns including distributed transactions, saga implementation, signal handling, and query patterns. Essential for building highly reliable, scalable, long-running backend systems, and mastering async/await execution models for production deployment.

This skill provides comprehensive, structured guidance for testing Temporal workflows written in Python. It covers best practices for unit testing (using time-skipping), integration testing (mocking dependencies), and determinism validation through replay testing. Ideal for ensuring high code coverage and robust CI/CD pipelines for complex asynchronous workflows.

Comprehensive guide for creating, managing, and automating preview deployments on Vercel. Learn how to utilize both the CLI and REST API to deploy unique, temporary environments for specific branches or pull requests. This is essential for pre-production testing, integrating into CI/CD pipelines, and sharing stable preview URLs with stakeholders before merging to main.

Provides durable workflow automation guidance for AI agents, covering platforms like n8n, Temporal, Inngest and patterns such as sequential, parallel, and orchestrator-worker flows to turn brittle scripts into production-grade orchestration.

Aeon is a scikit-learn compatible toolkit for time series machine learning, covering classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search, and feature extraction on temporal data.