Skill UI

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 comprehensive workflow manages the entire lifecycle of notes within Evernote. It provides structured methods for creating new notes (supporting plain text, checklists, and ENML formatting), retrieving existing content, updating notes, and organizing both notes and notebooks/stacks. Essential for building full-featured note-taking applications and content management systems.

Implement robust Role-Based Access Control (RBAC) specifically for Evernote integrations. This guide covers multi-tenant architectures, handling Evernote Business accounts, defining granular permissions (READ, WRITE, FULL), and creating authorization middleware. Essential for building secure, enterprise-grade SaaS applications that manage shared corporate data.

A comprehensive guardrail system for external search APIs (like Exa). It enforces content safety policies, manages domain access via allow/blocklists, sanitizes queries to prevent misuse, implements result freshness checks, and enforces per-user usage quotas. Essential for building reliable, secure, and cost-controlled integrations.

FAISS (Facebook AI Similarity Search) is a library designed for efficient similarity search and clustering of dense vectors. It supports indexing and searching on billions of vectors at scale, featuring GPU acceleration and multiple index types (Flat, IVF, HNSW, PQ) to balance speed and accuracy. It is essential for building high-performance, large-scale applications requiring fast k-NN retrieval or pure vector similarity matching, especially in fields like RAG and recommendation systems.

This skill guides the end-to-end development, deployment, and secure integration of complex AI features into Firebase applications. It covers setting up Cloud Functions, Firestore/Storage rules, Authentication, and connecting robustly with Vertex AI/Gemini for advanced AI capabilities. Focuses on building production-grade, highly secure, data-intensive AI systems.

This guide outlines essential security best practices for integrating Firecrawl. It covers secure API key storage (using environment variables and .gitignore), verifying webhook signatures with HMAC-SHA256 for data integrity, implementing key rotation strategies across different environments (dev/staging/prod), and sanitizing scraped content to mitigate XSS and PII risks. Essential for building secure, production-grade systems.

Provides a robust, event-driven reference architecture for building meeting intelligence platforms using Fireflies.ai. This guide details the full production pipeline, covering multi-source meeting ingestion (Zoom, Teams), webhook processing, and subsequent data enrichment into structured action items, analytics reports, and database storage. Ideal for designing complex integrations or advanced meeting analytics systems.

This guide provides comprehensive techniques for managing API rate limits and ensuring reliable, high-volume API usage with Gamma. It covers methods such as reading rate limit headers, implementing exponential backoff for automatic retries, and building robust request queuing systems to handle throttling gracefully.

A comprehensive guide providing reference architectural patterns for building scalable, maintainable, and robust enterprise integrations involving Gamma services. It details three patterns—Basic, Service Layer, and Event-Driven—covering use cases from simple prototypes to high-volume, microservices-based systems, guiding system designers and architects on best practices.

A comprehensive guide to building enterprise-grade AI applications using Firebase Genkit. This skill covers the full development lifecycle, including implementing advanced RAG systems, multi-step tool-calling agents, and complex workflows across Node.js, Python, and Go. It teaches best practices for schema validation (Zod/Pydantic), robust error handling, OpenTelemetry tracing, and deploying reliably to Firebase Functions or Cloud Run.

This skill guide helps developers master best practices and architectural patterns for Godot 4 game development using GDScript. It thoroughly covers implementing game systems, managing complex state machines, utilizing signals, and optimizing performance. Use this when building robust, scalable, or advanced Godot games.