Skill UI

This guide establishes a robust local development environment for Deepgram integrations. It covers setting up test fixtures using sample audio, mocking API responses for isolated unit testing, configuring watch-mode development servers, and running comprehensive unit and integration tests using Vitest. Use this setup when initiating a Deepgram feature or requiring a reliable, fast development cycle.

This skill provides a comprehensive and isolated setup for managing Deepgram API integrations across different deployment stages (Development, Staging, Production). It includes typed configuration management, a client factory pattern, and Docker Compose profiles, ensuring that each environment uses specific credentials, models, and feature settings (like diarization or PII redaction) without conflict. Ideal for robust, multi-stage application deployment.

Definition Of Done Generator auto-activates within Enterprise Workflows, guiding requests toward project management, compliance, and governance patterns while producing production-ready code, configurations, and validated outputs.

Automate deploying production-ready monitoring stacks like Prometheus, Grafana, and Datadog, delivering configuration files, deployment scripts, and guided instructions for infrastructure-focused observability setups.

A comprehensive expert for configuration management, specializing in validating, testing, and ensuring the correctness of application settings. It creates robust validation schemas (e.g., JSON Schema) and performs critical checks, including identifying potential security secrets (API keys, passwords), ensuring data consistency across different environments (development, staging, production), and enforcing type safety for reliable deployments.

Detects discrepancies between current infrastructure and desired configurations by running drift-detect, helping DevOps teams ensure Terraform-managed environments stay consistent and report configuration differences.

This skill defines a senior engineer specializing in the entire software development lifecycle (SDLC). It covers building robust CI/CD pipelines (e.g., GitHub Actions), containerizing applications with Docker, and managing infrastructure using Infrastructure as Code (IaC) tools like Terraform or Pulumi. Key areas include Kubernetes deployment (GitOps), cloud platform configuration (AWS/GCP/Azure), release automation, and incident response planning.

Provides practical advice on Dockerfiles, CI/CD pipelines, deployment strategies, infrastructure-as-code, and observability, helping teams containerize apps, configure GitHub Actions, plan production rollouts, and keep deployments secure and observable.

This skill acts as an expert guide for setting up comprehensive debugging environments, implementing distributed tracing solutions, and establishing robust diagnostic workflows. It is ideal for diagnosing complex, multi-service issues in development or production environments by standardizing logging, tracking correlation IDs, and ensuring end-to-end observability.

Guides automated distributed training setups with step-by-step practices, production-ready configs, and validation checks for ML training workflows.

Automates Docker Compose setup and best-practice guidance for DevOps basics, producing production-ready configurations and validating them against common standards.

Automates Docker Hub workflows through the Composio MCP integration, letting teams list organizations, create orgs and repositories, manage members and teams, and configure image-push webhooks for predictable deployments.