AI Analysis
Final verdict: SAFE
The package shows no signs of malicious activity or obfuscation. It does not make network calls or execute shell commands, and there is no evidence of credential harvesting.
- No network calls
- No shell execution
- No obfuscation
- No credential harvesting
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: No shell execution patterns detected, indicating the package does not execute external commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
Package Quality Overall: Low (1.2/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
○ Low
Documentation
1.0
No documentation detected
No documentation URL, doc files, or meaningful description found
○ 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 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 alizarin-clm
Create a fully-functional mini-application using the Python package 'alizarin-clm' which serves as a Controlled List Manager extension for Alizarin. This application will be called 'CLM Buddy'. Here’s a detailed plan on how to build it: 1. **Project Setup**: Initialize a new Python project. Install the required dependencies including 'alizarin-clm'. 2. **Core Functionality**: - Implement functions to create, read, update, and delete controlled lists. - Utilize 'alizarin-clm' to manage these operations efficiently. 3. **User Interface**: Develop a simple command-line interface (CLI) for interacting with 'CLM Buddy'. Users should be able to add items to a controlled list, view all items in a list, modify existing items, and remove items from a list. 4. **Advanced Features**: - Integrate a feature that allows users to categorize lists and filter items based on categories. - Add a search functionality to quickly find items within large lists. 5. **Data Persistence**: Ensure that the data managed by 'CLM Buddy' is saved and can be restored after the application is closed. Use file-based storage for simplicity. 6. **Error Handling**: Implement robust error handling to manage invalid inputs and operational errors gracefully. 7. **Testing**: Write unit tests to verify the correctness of each function provided by 'CLM Buddy'. 8. **Documentation**: Prepare a README file explaining how to install and use 'CLM Buddy', along with examples of common tasks. By the end of this project, you'll have a powerful yet easy-to-use tool for managing controlled lists, demonstrating the capabilities of 'alizarin-clm' in a practical context.