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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