amazon-quick

This is the official catalog repository for AWS Quick. It contains curated, skills, plugins, agents, and integration configs that can be installed into AWS Quick to extend its capabilities.

Drive Amazon Quick on macOS programmatically - desktop app and web, one protocol (Chrome DevTools Protocol). Send messages, read replies, build dashboards and apps, run deep research, manage spaces. Python + uv; login markers and start URL are configurable.

The Custom Connector Framework (CCF) is an open source AWS sample that simplifies building, running, and operating document ingestion from any document source into Amazon Bedrock knowledge bases, AWS Quick, or Amazon S3. You write the code that reads your source. CCF manages everything else a production connector needs.

7 open-source HR AI agents for the full employee lifecycle: hiring, onboarding, 9-box, rewards, org design, succession. Amazon Quick, Claude, ChatGPT.

Assignment Defender is an AI-Proofing Assistant. This page is its information hub with direct app access, walkthrough videos, sample assignment analyses, setup guidance, and AWS learning resources for designing more AI-robust assessments. This GitHub layout can be used as a template for faculty to share and demo similar AI innovations.

⚠️ Unofficial tool for simplified templating and sharing of kiro agent configs, steering files, skills and more

Conversational analytics with Amazon Quick on an Amazon S3, AWS Glue and Amazon Athena lakehouse. AWS CDK (Python) deploys Q Topics and a custom chat agent over synthetic card-payments data with embedded patterns you can test against.

Free prompt library, chapter guides and quiz for the book Amazon Quick for Business.

Run the Amazon Quick desktop app on Linux (unofficial). Builds from Amazon's official installer: native Electron UI + Windows helper under Wine, with automatic updates.

Custom AI skills and automation frameworks built with Amazon Quick

Connect Lark to the Model Context Protocol to bridge team communication with your local development environment.

Market Intelligence Agent project developed using Amazon Quick to analyze a Food Delivery dataset and external market research, identifying customer trends, competitive dynamics, market opportunities, market risks, and actionable business insights.

MCP Server wrapping lark-cli — let AI assistants (Quick, Claude, Cursor, Codex) operate Feishu/Lark without creating an app