asta-autodiscovery-modal

v0.1.5 safe
3.0
Low Risk

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🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks associated with it, showing no signs of malicious activity or poor coding practices. It appears to be a straightforward tool for integrating with Modal's AutoDiscovery feature.

  • No network calls detected
  • No shell executions detected
  • Low metadata quality but no clear malicious indicators
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell executions detected, indicating the package does not attempt to execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package shows some signs of low maintenance and metadata quality but does not exhibit clear malicious indicators.

📦 Package Quality Overall: Low (2.0/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (923 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low Type Annotations 1.0

No type annotations detected

  • No type annotations, py.typed marker, or stub files detected
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author "Allen Institute for Artificial Intelligence" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with asta-autodiscovery-modal
Create a web-based inventory management system using Python's Flask framework and the 'asta-autodiscovery-modal' package. This system should allow users to easily manage their inventory items through a user-friendly interface. Here are the key functionalities you need to implement:

1. **Inventory Item Management**: Users should be able to add, edit, delete, and view details of inventory items. Each item will have attributes like name, category, quantity, price, and description.
2. **Category Management**: Allow users to create, edit, delete, and view categories of inventory items. Categories help organize the items into meaningful groups.
3. **Search Functionality**: Implement a search feature that allows users to find specific items or categories based on keywords.
4. **User Authentication**: Ensure that only authenticated users can access the inventory management features. Use basic authentication for simplicity.
5. **Auto-Discovery Modal Integration**: Utilize the 'asta-autodiscovery-modal' package to enhance the user experience. Specifically, use it to automatically display modals when users perform certain actions such as adding a new item or editing an existing one. These modals should provide quick feedback or additional options relevant to the action being performed.
6. **Responsive Design**: Make sure the application is responsive and works well on both desktop and mobile devices.

The 'asta-autodiscovery-modal' package will be used to dynamically show modals based on user interactions without requiring manual intervention. For example, when a user clicks on the 'Add New Item' button, a modal should appear automatically to guide them through the process of adding a new item. Similarly, after an item is added or edited, a confirmation modal should pop up to notify the user about the successful operation. Your task is to integrate this package seamlessly into your Flask application to ensure a smooth and intuitive user experience.

💬 Discussion Feed

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