AI Analysis
Final verdict: SUSPICIOUS
The package has minimal technical risks but lacks essential metadata, suggesting it may not be well-maintained or trustworthy.
- Lack of maintainer history
- Missing author details
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 of command injection or similar vulnerabilities.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of low effort and could be suspicious due to the lack of maintainer history and missing author details.
Package Quality Overall: Low (1.2/10)
β Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
β Low
Documentation
1.0
No documentation detected
No documentation URL, doc files, or meaningful description found
β Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
β Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
β Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked β 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 8.0
4 maintainer concern(s) found
Only one version has ever been released β brand new packageAuthor 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 amolmath
Create a Python-based educational tool called 'MathMaster' that leverages the functionalities of the 'amolmath' package to assist students in mastering various mathematical concepts. The app should serve as both a learning aid and a practice platform, offering interactive lessons and quizzes on fundamental math topics such as arithmetic, algebra, and geometry. Here are the key steps and features for developing MathMaster: 1. **Setup Project Environment**: Begin by setting up your Python development environment. Ensure you have the 'amolmath' package installed. If 'amolmath' does not have a public repository or documentation, assume it includes functions for generating random math problems, checking answers, and providing explanations for solutions. 2. **Core Features**: - **Interactive Lessons**: Develop modules within MathMaster that cover different math topics. Each module should include brief explanations, examples, and interactive elements where users can input answers and receive immediate feedback. - **Random Problem Generator**: Utilize 'amolmath' to create a feature that generates random math problems tailored to the userβs current level of understanding. Problems should range from simple arithmetic operations to more complex algebraic equations based on the difficulty settings chosen by the user. - **Practice Mode**: Implement a practice mode where users can solve generated problems at their own pace. This mode should track correct answers and provide explanations for any incorrect responses, using 'amolmath' capabilities. - **Quiz Mode**: Design a timed quiz mode that tests the userβs knowledge across multiple topics. After completing a quiz, provide a detailed score report and explanations for all questions. 3. **User Interface**: While MathMaster can start as a command-line interface (CLI), consider expanding it to include a graphical user interface (GUI) for a more engaging experience. For the CLI version, ensure commands are intuitive and well-documented. 4. **Feedback Mechanism**: Integrate a feedback system that allows users to rate the difficulty of problems and suggest improvements. Use this data to refine the problem generation algorithm within 'amolmath'. 5. **Progress Tracking**: Enable users to track their progress over time through saved sessions and performance metrics. This could include graphs showing improvement trends in specific areas of math. 6. **Educational Content**: Ensure that the content provided is accurate and aligned with common educational standards. Consider collaborating with educators to review and improve the quality of educational materials. 7. **Testing & Deployment**: Thoroughly test MathMaster to ensure all features work as expected. Deploy the application so it can be easily accessed by students and educators worldwide. By following these steps and leveraging the unique features of 'amolmath', you will create a valuable tool that enhances math education and supports learners at all levels.
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