AI Analysis
The package shows low risks in terms of network, shell, and obfuscation activities, but it lacks maintainer history and a GitHub repository, raising concerns about its legitimacy and potential maintenance.
- Lack of maintainer history
- Absence of a GitHub repository
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell executions detected, indicating no direct system command invocations.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package appears suspicious due to its lack of maintainer history and the absence of a GitHub repository, indicating potential risk.
Package Quality Overall: Low (2.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (3416 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
50 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
Email domain looks legitimate: web.de>
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
3 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Your task is to develop a command-line utility called 'EvoTuner' using Python and the 'audient-evo-linux' package. This utility will allow users to control various audio settings of their Audient EVO series interfaces (EVO4, EVO8, EVO16) directly from the terminal. The application should be user-friendly, allowing users to easily adjust input/output levels, monitor selections, and even toggle phantom power for microphones. Here are the key steps and features you need to implement: 1. **Setup**: Ensure your environment has Python and the 'audient-evo-linux' package installed. The package provides access to the hardware's capabilities through a set of Python functions. 2. **Main Menu**: Create a simple menu system where users can navigate through different options like 'Input Controls', 'Output Controls', 'Monitor Settings', and 'Advanced Features'. 3. **Input Controls**: Users should be able to set input gain levels for each channel and toggle phantom power for microphone inputs. Display current settings alongside options for adjustment. 4. **Output Controls**: Implement functionality to control output volume levels for each channel. Include an option to mute/unmute outputs. 5. **Monitor Settings**: Allow users to switch between different monitor setups and adjust the monitor mix level. 6. **Advanced Features**: Offer more complex operations such as setting up custom equalization curves or accessing low-level mixer controls. 7. **Help & Exit**: Provide a help section explaining all commands and an exit option to safely close the program. The 'audient-evo-linux' package simplifies interaction with the EVO series hardware, enabling direct access to its functionalities via Python. Your goal is to create a robust, easy-to-use interface that leverages this package's capabilities to provide a comprehensive control solution for Audient EVO series users.
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