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Amplitude Automation Toolkit

amplitude-automation

davepoon/buildwithclaude

Automate Amplitude analytics tasks through Composio’s Rube MCP toolkit, covering event ingestion, user activity, property management, cohorts, and schema discovery before each call.

Amplitude Automation Toolkit

amplitude-automation

davepoon/buildwithclaude

Automate Amplitude analytics tasks through Composio’s Rube MCP toolkit, covering event ingestion, user activity, property management, cohorts, and schema discovery before each call.

Azure Monitor Java SDK

azure-monitor-ingestion-java

sickn33/antigravity-awesome-skills

Java SDK for sending custom logs to Azure Monitor via Data Collection Rules and Endpoints, offering synchronous, asynchronous, batching, concurrency, and error-handling workflows to reliably ingest logs into Log Analytics.

Azure Monitor Ingestion SDK

azure-monitor-ingestion-py

sickn33/antigravity-awesome-skills

Azure Monitor Ingestion SDK for Python lets you authenticate via DefaultAzureCredential and push custom logs to a Log Analytics workspace through the Logs Ingestion API with sync or async clients, automatic batching, gzip compression, retries, and error callbacks.

Azure Monitor Query SDK

azure-monitor-query-java

sickn33/antigravity-awesome-skills

Deprecated Azure Monitor Query SDK for Java that runs Kusto queries against Log Analytics workspaces and Azure resources, covering both Logs and Metrics with sync/async clients and sovereign cloud endpoints.

Azure Monitor Query SDK for Python

azure-monitor-query-py

sickn33/antigravity-awesome-skills

A comprehensive Python SDK for interacting with Azure Monitor services. It enables developers to execute complex Kusto Query Language (KQL) queries against Log Analytics workspaces and retrieve various resource metrics (CPU usage, network traffic, etc.). Ideal for building robust monitoring dashboards, automated alerting systems, and custom data analysis pipelines in cloud environments.

Azure Data Lake SDK

azure-storage-file-datalake-py

sickn33/antigravity-awesome-skills

Azure Data Lake Storage Gen2 SDK for Python enables hierarchical file system management, ACL control, metadata handling, and async transfers for big data analytics workflows hosted in Azure Storage.

ClickHouse Analytics and Data Engineering Patterns

cc-skill-clickhouse-io

sickn33/antigravity-awesome-skills

This guide provides comprehensive patterns and best practices for working with ClickHouse, a high-performance OLAP database. It covers advanced topics such as MergeTree engine design, efficient query optimization (filtering, aggregations, window functions), bulk/streaming data ingestion, materialized view creation, and performance monitoring techniques, ensuring optimal performance for large-scale analytical workloads.

ClickHouse Analytics Patterns

affaan-m/everything-claude-code

Guides ClickHouse database architects through schema designs, query optimization, ingestion strategies, and monitoring techniques tailored for high-performance analytical workloads.

Customerio Webhook Events

customerio-webhooks-events

jeremylongshore/claude-code-plugins-plus-skills

Implement full Customer.io webhook handling covering email, push, SMS, and in-app events, with signature verification, reliable queueing, reporting API calls, and optional BigQuery streaming for analytics.

Data Engineering Patterns

data-engineering

rohitg00/awesome-claude-code-toolkit

Guides data engineering patterns for ETL pipelines, Spark analytics, and quality checks, showcasing Python and SQL snippets to extract, transform, load, validate, and model sales data in modern warehouses.

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.

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