Skill UI

A comprehensive guide for configuring localization services (Lokalise) across multiple deployment environments (development, staging, production). It details two strategies: dedicated projects or single-project branching. Focuses heavily on secure secret management using tools like AWS Secrets Manager, GCP Secret Manager, and HashiCorp Vault, ensuring that environment-specific configurations and translations remain isolated throughout the CI/CD pipeline.

A comprehensive guide for configuring and managing multiple, isolated deployment environments (development, staging, production) for SaaS applications. It covers best practices such as using environment variables for configuration, implementing client factories for resource isolation, integrating secure secret management (e.g., GCP Secret Manager), and running validation scripts to ensure consistency and security across all deployment stages.

Helps manage container registries like AWS ECR, Google GCR, and Harbor by generating configuration code, guiding access controls, and advising best practices for secure, production-ready image storage and deployment automation.

Automates GCP Memorystore configuration by guiding users through best-practice patterns, generating production-ready resources, and validating outputs whenever the skill detects memorystore config queries.

This guide provides comprehensive instructions for installing and configuring the official Mistral AI SDK (for both Python and Node.js). It covers setting up API keys via environment variables, verifying the connection, and implementing secure credential storage using Secret Managers (GCP/AWS) for production environments. Ideal for starting any new Mistral AI project.

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.

This skill provides a comprehensive decision framework and set of patterns for architects designing cloud-agnostic applications across major providers like AWS, Azure, and GCP. It details service comparisons (Compute, Storage, DB), multi-cloud patterns (e.g., Best-of-Breed, DR), cost optimization strategies, and structured migration plans, ensuring robust and resilient enterprise deployments.

Automated guidance for configuring Pub/Sub subscriptions within GCP, offering step-by-step best practices, production-ready configurations, and validation against common standards whenever you mention subscription config requests.

Automates Google Cloud Pubsub topic setup with step-by-step guidance, best practices, production-ready configurations, and validation tailored for GCP skills workflows.

Automate RingCentral calls, messages, meetings, and unified communications with Composio’s Rube MCP toolkit by discovering current tool schemas, executing multi-step workflows, validating inputs, handling pagination, and maintaining active connections before each run.

Summarizes the RingCentral automation toolkit status in Composio, noting the lack of RING_CENTRAL tools and how to watch RUBE discovery plus fallback toolkits.

A comprehensive guide to implementing secure secrets management practices for Continuous Integration/Continuous Deployment (CI/CD) pipelines. It covers using industry-leading tools like HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, and GCP Secret Manager to securely store, retrieve, and automatically rotate credentials (API keys, database passwords, TLS certificates) without hardcoding them into source code. Includes best practices for least-privilege access and audit logging.