Skill UI

Memory provides persistent context across multiple coding sessions. It stores crucial project decisions, user preferences (like preferred package managers or specific libraries), and architectural conventions in a local memory file. This ensures that the AI maintains consistency, recalls past choices automatically, and applies project-specific rules without needing constant reminders, significantly improving workflow continuity and reliability.

This skill acts as a specialized expert for generating professional and complex diagrams using Mermaid syntax. It specializes in creating flowcharts, sequence diagrams, ERDs, state charts, Gantt charts, and various system architectures. It adheres to best practices, ensuring readability, consistent styling, and providing complete, ready-to-use code for multiple diagram types.

This skill provides a comprehensive framework for mastering microservices architecture patterns. It covers critical aspects of building robust, distributed systems, including defining service boundaries (Domain-Driven Design), managing inter-service communication, handling distributed data transactions, and implementing various resilience patterns (e.g., circuit breaker, circuit breaker). It is essential for large-scale system decomposition.

Guides production-grade miles RL training for massive MoE models, covering FP8/INT4 low precision, train-inference alignment, and speculative rollout workflows to maximize throughput in enterprise deployments.

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.

This comprehensive skill guides developers through major version upgrades of the Mistral AI SDK. It specifically detects breaking changes, such as the shift from CommonJS to ESM, and provides detailed steps, automated code transformation scripts, and best practices for migrating existing code. Use this when jumping major SDK versions or refactoring complex Mistral integrations to ensure a smooth transition to the latest API.

This comprehensive guide covers the entire MLOps lifecycle, specializing in building robust, scalable, and production-grade Machine Learning systems. Expertise includes orchestrating complex ML pipelines using Kubeflow, Airflow, Prefect, and cloud-native services (AWS SageMaker, Azure ML, GCP Vertex AI). It covers experiment tracking (MLflow, W&B), model versioning, model registries, infrastructure as code (Terraform), and container deployment using Kubernetes. Ideal for engineers tasked with moving ML models from research to reliable, managed production environments.

Mastery of modern mobile development across multiple platforms, including React Native, Flutter, and native iOS/Android. Expertise covers the entire lifecycle, specializing in architectural patterns (Clean, MVVM), performance optimization, offline-first data synchronization (GraphQL, SQLite), advanced DevOps practices (CI/CD, Fastlane), and App Store Optimization (ASO). Ideal for building robust, scalable, and highly performant cross-platform applications.

This guide provides comprehensive principles for developing games specifically for mobile platforms. It covers essential technical constraints and best practices, including optimizing for touch input, managing battery life and thermal performance, adhering to platform-specific requirements (iOS/Android), and selecting appropriate monetization models. Use this when designing highly optimized, user-centric mobile gaming experiences.

This expert specializes in secure mobile development practices, covering areas like input validation, WebView security, secure data storage (KeyStore/Keychain), and advanced network security (Certificate Pinning). Use this skill to write secure, resilient mobile code for both iOS and Android, mitigating platform-specific vulnerabilities and ensuring sensitive data protection.

Automatically generates robust, schema-compliant mock API servers directly from OpenAPI specifications. This tool supports advanced testing features, including stateful CRUD operations, Faker-driven dynamic data generation, configurable latency simulation, and detailed request recording for contract testing. Ideal for frontend parallel development and isolated integration testing.

Automates Moz tasks through Composio’s Rube MCP workflow by discovering tool schemas, validating toolkit connections, and sequencing multi-step executions while respecting session and memory requirements.