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Database Schema Designer

database-schema-designer

jeremylongshore/claude-code-plugins-plus-skills

Automates database schema design guidance for backend projects, activating whenever you ask about schema patterns, best practices, or implementation in node.js, Python, Go, microservices, caching, or messaging contexts.

Database Test Helper

database-test-helper

jeremylongshore/claude-code-plugins-plus-skills

Automates database-focused test work by offering best-practice guidance, fixtures, and configurations for unit, integration, and mocking scenarios in test automation workflows.

Databricks CI Integration

databricks-ci-integration

jeremylongshore/claude-code-plugins-plus-skills

Automates Databricks bundle validation, notebook unit tests, staging deployments, and production rollouts via GitHub Actions; ideal when you want repeatable CI/CD coverage for Databricks workspaces.

Databricks Debug Bundle

databricks-debug-bundle

jeremylongshore/claude-code-plugins-plus-skills

Automates gathering Databricks diagnostic data—cluster info, job runs, Spark logs, Delta tables, configs, and connectivity checks—to speed support ticket preparation and recurring troubleshooting workflows.

Databricks Multi Environment Setup

databricks-multi-env-setup

jeremylongshore/claude-code-plugins-plus-skills

Guides setting up Databricks with separate configs, API keys, and secrets for development, staging, and production, plus CI/CD-aware environment resolution.

Databricks Observability Guide

databricks-observability

jeremylongshore/claude-code-plugins-plus-skills

Provides Databricks monitoring instructions using system tables, SQL alerts, and the SDK to track job health, cluster utilization, query performance, costs, and exportable metrics for observability-driven operations.

Databricks Deploy Checklist

databricks-prod-checklist

jeremylongshore/claude-code-plugins-plus-skills

Guided checklist covering Databricks production deployments, from security and infrastructure prep through testing, job configuration, monitoring, and rollback commands, so teams can trigger go-live work with validated bundles and recovery steps.

Databricks Reference Architecture

databricks-reference-architecture

jeremylongshore/claude-code-plugins-plus-skills

Guides teams through the Databricks reference architecture with lakehouse layers, Unity Catalog governance, project layout conventions, and CI/CD integration for production analytics platforms.

Databricks SDK Patterns

databricks-sdk-patterns

jeremylongshore/claude-code-plugins-plus-skills

Apply production-ready Databricks SDK patterns for Python and REST integrations, outlining singleton clients, structured error handling, retries with exponential backoff, context managers, and fluent job builders to keep workflows reliable.

Datadog Automation Hub

datadog-automation

davepoon/buildwithclaude

Automates Datadog monitoring workflows via Composio’s Rube MCP, letting you query metrics, search logs, manage monitors and dashboards, and create events or downtimes after connecting to the MCP toolkit and tools list.

Datagma Automation Workflow

datagma-automation

ComposioHQ/awesome-claude-skills

Guides using Rube MCP’s Composio toolkit to discover current Datagma tools, verify connections, and execute workflows while adhering to live schemas, session reuse, and required memory parameters.

DBOS Go Best Practices for Workflows

sickn33/antigravity-awesome-skills

This guide provides best practices for developing reliable, fault-tolerant Go applications using DBOS durable workflows. It covers critical aspects such as application initialization, registering workflows, structuring steps, using queues for concurrency control, and maintaining determinism. Essential for developers integrating DBOS into existing Go codebases.

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