AI Analysis
The package appears mostly benign with no detected network, shell, or obfuscation risks. However, the missing repository and single-package maintainer raise concerns about potential supply-chain attacks.
- Repository not found
- Maintainer has only one package
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires internet access to function properly.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands, which is typical and safe.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The repository is not found and the maintainer has only one package, which could indicate suspicious activity.
Package Quality Overall: Low (3.8/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Detailed PyPI description (1982 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
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
Email domain looks legitimate: autonoma.ai
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
1 maintainer concern(s) found
Author "Autonoma AI" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a fully functional mini-application that leverages the Autonoma SDK (package name: autonoma-ai) to streamline the process of managing environments for software development teams. This application will serve as a powerful tool for developers and DevOps engineers, enabling them to automate the creation, management, and deletion of development environments directly from their local machines or CI/CD pipelines. ### Application Overview: Your task is to develop a Python-based command-line interface (CLI) application that integrates with the Autonoma SDK to manage environments. The application should allow users to: - List all available environments. - Create new environments based on predefined templates. - Delete existing environments. - Update environment configurations. - Retrieve details about specific environments. ### Core Features: 1. **Environment Management**: Users should be able to create, delete, and update environments. Each environment should have a unique identifier and can be associated with various configurations such as machine type, storage size, etc. 2. **Template Support**: Integrate support for multiple environment templates. These templates should be customizable and reusable across different projects. 3. **CLI Commands**: Design a set of intuitive CLI commands for each action. For example, `autonoma list`, `autonoma create`, `autonoma delete`, etc. 4. **Configuration File**: Allow users to store their API keys and default settings in a configuration file to avoid hardcoding sensitive information. 5. **Logging and Error Handling**: Implement logging for all actions performed through the CLI. Additionally, provide clear error messages for any failures during execution. 6. **Help Documentation**: Include a help command (`autonoma help`) that provides usage instructions and examples for each feature. ### Utilizing the 'autonoma-ai' Package: To achieve these functionalities, you will need to utilize the Autonoma SDK (autonoma-ai). This package offers a Python interface to interact with the Autonoma Environment Factory endpoint. Your application will use this SDK to authenticate users, send requests to the factory endpoint, and handle responses. Make sure to document how the SDK is integrated into your application, including how it handles authentication and data serialization/deserialization. ### Additional Considerations: - Ensure the application is well-documented and easy to install via pip. - Provide sample usage scenarios and scripts for common tasks. - Consider adding a feature to schedule environment creation/deletion for recurring tasks. This project aims to demonstrate the power of automation in modern software development practices while providing a practical tool for developers and DevOps teams.
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