🤖 AI Analysis

Final verdict: SAFE

The package appears safe with low risk scores across all analyzed categories. There are no indications of malicious activity or supply-chain attacks.

No network calls detected
No shell execution patterns
No obfuscation techniques used
No credential harvesting attempts

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no immediate risk from command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.

📦 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

Brief PyPI description (364 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 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" 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 algomancy-quickstart

Your task is to develop a simple yet powerful command-line tool using the 'algomancy-quickstart' Python package. This tool will streamline the process of setting up a new Algomancy application for data scientists and developers who wish to leverage machine learning models without deep expertise in model training and deployment. Your application, named 'QuickMLBoot', should guide users through the setup process interactively and provide options to customize their ML environment according to specific needs.

Here’s a breakdown of the steps your application should take:
1. **Welcome Message**: Start by greeting the user and explaining the purpose of QuickMLBoot.
2. **Project Setup Wizard**: Use 'algomancy-quickstart' to guide the user through the setup process. This includes selecting the type of ML project (classification, regression, clustering, etc.), specifying dependencies, and choosing between local or cloud-based deployments.
3. **Customization Options**: Allow users to customize their project by adding specific libraries, adjusting configurations, and setting up environments (e.g., virtualenv).
4. **Finalize Setup**: Once all selections are made, finalize the setup by generating necessary files, installing dependencies, and providing instructions on how to run and manage the project.
5. **Post-Setup Instructions**: After setup, offer additional resources such as documentation links, community support details, and tips for further customization and optimization.

Suggested Features:
- Support for multiple ML frameworks (TensorFlow, PyTorch, Scikit-Learn)
- Integration with popular cloud services (AWS, Google Cloud, Azure)
- Pre-configured templates for common use cases
- User-friendly CLI interface with clear prompts and error messages
- Detailed logging and feedback during the setup process

Utilize the 'algomancy-quickstart' package to handle the interactive CLI wizard and automation tasks, ensuring a smooth and efficient setup experience for users. Your goal is to create a tool that not only sets up projects quickly but also empowers users to tailor their ML environments effectively.