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Ziggy is an innovative system designed to streamline data management and automation for personal projects, team collaborations, and organizational efficiency. It leverages GitHub workflows, seamless integrations, and intelligent automation, simplifying complex operations and making the system a valuable asset.

The system focuses on automating routine tasks such as data synchronization, archival, and cleanup. Additionally, Ziggy efficiently manages dynamic data files like data.json, supporting versioning and remote updates. Users can also create flexible workflows to handle custom operations, such as purging outdated files and archiving critical data.

Initially, all functionalities were consolidated in a single file, but this setup encountered memory limitations with ChatGPT, leading to occasional data loss. To address this, the system evolved to use a private custom GPT. This adaptation allowed key files that control overall behavior to be attached as immutable knowledge, ensuring they are not lost. Meanwhile, the data file, being smaller and more dynamic, became easier to manage.

The integration of a GitHub repository has been pivotal, acting as a long-term memory aid and providing a means to recover forgotten data.json information. This setup intentionally avoids the use of databases or middleware to keep the system as straightforward as possible.

Ziggy is open for further experimentation. It is designed to be adaptable, allowing users to integrate additional tools such as Google Calendar or IFTTT, or to transition the system to other platforms like GitLab or BitBucket with the help of ChatGPT.

While it's acknowledged that some aspects may have been overlooked, the groundwork laid by Ziggy provides a robust base from which users can expand and direct their projects effectively, demonstrating a streamlined and innovative use of technology in data management and automation. If you do get stuck, I will be honest, I was able to use the o1 models with improved logic handling to get most of my questions answered and provisioned desired guidance.

CORE FEATURES:

1. Dynamic Data Handling: Ziggy supports robust handling of JSON files, allowing users to modify, publish, and archive data effortlessly.
2. GitHub Workflows: The system uses advanced GitHub Actions workflows (archivedata, purgedata, etc.) for seamless automation and error handling.
3. Error Logging and Notifications: Built-in mechanisms notify users of issues, ensuring transparency and quick resolution.
4. Customizable Automation: Ziggy’s workflows can be tailored to fit various use cases, from personal to professional applications.

Ziggy’s architecture ensures reliability, scalability, and ease of use, making it ideal for both beginners and advanced users seeking a simplified yet capable solution.