Skill UI

This skill covers persistent memory systems for Large Language Model (LLM) conversations. It includes implementing short-term, long-term, and entity-based memory to enhance context retention across sessions. Features include memory consolidation, retrieval strategies, and integrating memory into prompts. Suitable for building conversational AI applications using tools like Mem0, LangChain, or Redis.

Design collaborative AI agent teams with CrewAI: define agent roles, goals and backstories, build dependent tasks, and orchestrate crews via sequential or hierarchical processes with memory, tools, planning and flows.

A framework for building production-ready, low-latency, multimodal AI agents. It allows developers to orchestrate complex pipelines that seamlessly handle real-time audio, video, and text data. Key capabilities include integrating multiple AI services (LLMs, STT, TTS), managing conversation context, and enabling tool use and function calling for advanced, interactive AI applications.

This comprehensive workflow guides the entire database lifecycle, from initial architecture design (covering both SQL and NoSQL) to advanced implementation, optimization, and maintenance. It covers crucial stages like schema design, implementing migrations, optimizing query performance, developing robust data pipelines (using tools like Airflow and dbt), and managing data quality and operations. Ideal for engineers building complex, production-grade data systems.

This skill enables the creation of comprehensive monitoring solutions for database migrations. It covers Change Data Capture (CDC) pipelines, real-time data synchronization, anomaly detection, and automated alerting. You will learn to build observability infrastructure using tools like Prometheus, Grafana, Kafka, and Debezium to track migration metrics, document processing, and replication lag in enterprise environments.

A guide to production-ready patterns for dbt (data build tool). It covers essential practices for robust data pipeline development, including model organization (staging, intermediate, marts), implementing advanced testing strategies, ensuring data quality, and optimizing incremental processing for large datasets.

Specialist in reducing developer friction, automating repetitive tasks, and improving development workflows. Analyzes current setup, identifies pain points, and implements incremental improvements to tooling, scripts, documentation, and IDE configuration. Use for onboarding, build/test feedback, and repeatable scripts.

Provides comprehensive guidance on building robust evaluation frameworks for complex agent systems. It addresses the inherent challenges of non-determinism and multiple valid paths, enabling systematic performance testing, validating context engineering choices, and measuring continuous improvements across multiple quality dimensions (e.g., factual accuracy, tool efficiency).

This skill provides curated guidance for building high-performance animations in Expo and React Native. It covers hard rules for animation necessity, tool selection like Reanimated 4, and performance optimization for real devices. Use this when implementing motion that survives strict reviews on actual hardware, focusing on worklets, UI runtime, and gesture handling.

A comprehensive toolkit for accelerating digital product growth. It covers essential strategies including growth hacking, SEO/ASO optimization, building viral loops, email marketing funnels, CRM implementation, and analyzing the entire customer acquisition lifecycle using AARRR metrics. Ideal for product managers and marketers aiming for exponential business expansion.

Build container-based hosted agents using Azure AI Projects SDK with HostedAgentDefinition. Covers installation, environment setup, authentication, core workflow, resource allocation, and tool configuration for Azure AI Foundry.

Create reusable command-line scripts and utilities for the Hugging Face API, enabling chaining, piping, and intermediate processing. Supports direct API access and the hf CLI tool, with examples for model search, metadata enrichment, and model card parsing.