Skill UI

A comprehensive guide to implementing robust, multi-layered API response caching using distributed stores like Redis and Memcached, alongside CDN integration. Learn advanced strategies such as tag-based cache invalidation, read-through/write-through patterns, TTL management, and serving stale-while-revalidate content to drastically boost application performance and scalability.

Automates designing and implementing table partitioning strategies to keep large databases performant, optimize time-series workloads, and shorten maintenance windows, with guidance on key selection, SQL scripts, and query tuning.

This comprehensive skill manages the entire lifecycle of database testing, ensuring data integrity and system reliability. It covers setting up isolated test environments (using Docker or in-memory databases), executing migrations, and implementing robust test isolation strategies (such as transaction rollback). Use cases include verifying CRUD operations, validating referential constraints, performance benchmarking (EXPLAIN ANALYZE), and ensuring backward compatibility across multiple databases (PostgreSQL, MySQL, MongoDB) and ORMs.

Manages SSL/TLS certificates via the ssl-certificate-manager plugin by checking expiry dates, renewing certificates, listing installations, and reporting results to keep connections secure and troubleshooting informed.

Automates the setup of memory profilers for performance testing workflows, guiding users through best practices, code/configuration generation, and validation against industry standards whenever memory profiler setup is mentioned.

This skill provides methodologies for designing sophisticated, layered memory architectures for AI agents. It moves beyond simple context windows and basic vector stores by incorporating short-term, long-term, and graph-based memory systems. Implementing this is crucial for agents that require persistence across sessions, maintaining complex entity consistency, and performing advanced, relationship-driven reasoning over accumulated knowledge bases, including time-aware fact tracking.

Auto-activating skill guiding metadata extractor implementations within data pipelines, covering ETL, transformation, orchestration, and streaming best practices.

This skill outlines a comprehensive, low-downtime process for migrating APIs between different versions, frameworks, or platforms. It guides the implementation of advanced architectural patterns like the Strangler Fig pattern, traffic shadowing, and canary deployments. Use this when upgrading a monolithic API to microservices or transitioning between incompatible API versions.

A comprehensive guide and expertise source for developing robust, high-performance Minecraft server plugins using Bukkit, Spigot, and Paper APIs. Covers advanced topics including event handling, NMS internals, performance profiling, architecture design (SOLID), and ecosystem integration (Redis, Docker). Ideal for complex, production-grade plugin development.

This comprehensive guide details the deployment process for Mistral AI-powered applications across various cloud and container platforms, including Vercel, Docker, Google Cloud Run, and self-hosted vLLM setups. It covers secure API key management, platform-specific secret configuration, and the full steps required to establish robust, scalable production pipelines for your AI model.

A comprehensive guide to establishing a fast, reproducible local development lifecycle for Mistral AI integrations. This workflow includes setting up project scaffolding, implementing hot reloading with tsx, performing unit tests with Vitest mocking, and executing live integration tests against the Mistral API. Ideal for setting up reliable AI application development environments.

This skill provides a comprehensive framework for monitoring Mistral AI API usage in production. It includes an instrumented client wrapper (TypeScript) to automatically capture critical metrics like latency, token consumption, cost, and error rates. Furthermore, it integrates with Prometheus for metric storage and Grafana for visualization, allowing users to set up sophisticated alerting rules for performance degradation, rate limiting, or cost spikes.