AI Analysis
The package appears to be a placeholder with low effort in creation, raising concerns about its legitimacy and intent. However, there are no immediate signs of malicious activity.
- Metadata risk due to low effort in creation
- Placeholder nature of the package
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access for its functionality.
- Shell: No shell execution patterns detected, indicating no direct system command execution by the package.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
- Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
- Metadata: The package shows signs of low effort and possibly being newly created, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (1.2/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "Alex Ngai" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a fully-functional mini-app using the Python package 'autonomation' which aims to automate repetitive tasks and enhance productivity. The app should be designed to help users manage their daily tasks more efficiently. Here are the steps and features you need to include: 1. **Task Creation**: Users should be able to create new tasks, specifying the task name, description, due date, and priority level. 2. **Task Scheduling**: Implement a feature where users can schedule tasks to repeat at regular intervals, such as weekly or monthly. 3. **Reminders**: Set up reminders for upcoming tasks via email or SMS notifications, based on user preferences. 4. **Progress Tracking**: Allow users to mark tasks as completed and track their progress over time. 5. **Analytics Dashboard**: Develop an analytics dashboard that provides insights into task completion rates, time spent on tasks, and other relevant metrics. 6. **Integration with Calendar Apps**: Integrate the app with popular calendar applications like Google Calendar to synchronize tasks automatically. 7. **User Interface**: Design a simple and intuitive user interface using a web framework like Flask or Django. **How 'autonomation' is Utilized**: - Use 'autonomation' to handle the automation of task scheduling and reminder notifications. - Leverage its features to ensure seamless integration with external services and tools. - Employ 'autonomation' for data processing and analytics to provide meaningful insights to users. This project will not only demonstrate the capabilities of 'autonomation' but also offer a practical solution for managing daily tasks.
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