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WCAG Accessibility Guide
accessibility-wcag
rohitg00/awesome-claude-code-toolkit
233
Outlines WCAG 2.2 accessibility patterns for web apps, covering semantic HTML, ARIA roles, keyboard navigation, form handling, and contrast checks to keep interfaces usable for assistive technologies.
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Project Analysis Guide
analyzing-projects
CloudAI-X/claude-workflow-v2
255
Guides a structured walkthrough for onboarding into unfamiliar codebases by covering quick overviews, stack detection, directory mapping, pattern spotting, workflow checks, and summary reporting so teams can answer "how does this work" with confidence.
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Authentication Strategy Guide
authentication-patterns
rohitg00/awesome-claude-code-toolkit
498
Overview of secure authentication and authorization patterns covering JWT access/refresh flows, middleware enforcement, OAuth2 PKCE login, RBAC permissions, and anti-patterns/checklists for modern web apps.
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Authentication Strategy Guide
authentication-patterns
rohitg00/awesome-claude-code-toolkit
498
Overview of secure authentication and authorization patterns covering JWT access/refresh flows, middleware enforcement, OAuth2 PKCE login, RBAC permissions, and anti-patterns/checklists for modern web apps.
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Detecting Anomalies with Azure AI Java
azure-ai-anomalydetector-java
sickn33/antigravity-awesome-skills
300
This SDK allows developers to build robust anomaly detection applications in Java using Azure AI services. It supports both univariate and multivariate time-series analysis, enabling detection of outliers, trend changes, and correlated signals over large datasets. Ideal for real-time monitoring, operational intelligence, and advanced data quality checks.
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Detecting Anomalies with Azure AI Java
azure-ai-anomalydetector-java
sickn33/antigravity-awesome-skills
300
This SDK allows developers to build robust anomaly detection applications in Java using Azure AI services. It supports both univariate and multivariate time-series analysis, enabling detection of outliers, trend changes, and correlated signals over large datasets. Ideal for real-time monitoring, operational intelligence, and advanced data quality checks.
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Azure Event Hubs .NET Messaging SDK
azure-eventhub-dotnet
sickn33/antigravity-awesome-skills
212
A high-throughput SDK for .NET applications to connect with Azure Event Hubs. This library enables reliable event publishing, supporting efficient batching and buffered sending for high-volume data streams. It also provides a robust, production-grade event consumption mechanism using EventProcessorClient, which manages checkpointing and ensures scalable, real-time data pipeline integration. Ideal for building microservices and streaming architectures.
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Azure Event Hubs .NET Messaging SDK
azure-eventhub-dotnet
sickn33/antigravity-awesome-skills
212
A high-throughput SDK for .NET applications to connect with Azure Event Hubs. This library enables reliable event publishing, supporting efficient batching and buffered sending for high-volume data streams. It also provides a robust, production-grade event consumption mechanism using EventProcessorClient, which manages checkpointing and ensures scalable, real-time data pipeline integration. Ideal for building microservices and streaming architectures.
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Azure Event Hubs Streaming With Java
azure-eventhub-java
sickn33/antigravity-awesome-skills
183
This library offers comprehensive Java clients for interacting with Azure Event Hubs. It enables developers to build robust, high-throughput, real-time streaming applications and event-driven architectures. Features include sending single events, batching events, sending to specific partitions, and using the production-grade EventProcessorClient with checkpointing for reliable data processing.
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Azure Event Hubs Streaming With Java
azure-eventhub-java
sickn33/antigravity-awesome-skills
183
This library offers comprehensive Java clients for interacting with Azure Event Hubs. It enables developers to build robust, high-throughput, real-time streaming applications and event-driven architectures. Features include sending single events, batching events, sending to specific partitions, and using the production-grade EventProcessorClient with checkpointing for reliable data processing.
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Azure Event Hubs Python Streaming Client
azure-eventhub-py
sickn33/antigravity-awesome-skills
131
This SDK provides comprehensive Python support for interacting with Azure Event Hubs, a high-throughput streaming platform. It allows developers to build robust data ingestion pipelines, acting as both event producers (sending data) and event consumers (receiving data). Key features include efficient batch processing, partition key management, and reliable checkpointing using Azure Blob Storage for production-grade stream applications.
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Azure Event Hubs Python Streaming Client
azure-eventhub-py
sickn33/antigravity-awesome-skills
131
This SDK provides comprehensive Python support for interacting with Azure Event Hubs, a high-throughput streaming platform. It allows developers to build robust data ingestion pipelines, acting as both event producers (sending data) and event consumers (receiving data). Key features include efficient batch processing, partition key management, and reliable checkpointing using Azure Blob Storage for production-grade stream applications.
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