assignment-generator-sebastian-stigler

v0.3.1 safe
3.0
Low Risk

Assignment generator scaffold project

🤖 AI Analysis

Final verdict: SAFE

The package appears to be safe based on the lack of network calls, shell executions, obfuscations, and credential risks. However, the metadata suggests a lower level of effort, which raises some concern about its origin.

  • Low risk scores across all categories
  • Metadata indicates potential low-effort development
Per-check LLM notes
  • Network: No network calls detected, which is normal for most utility packages.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, indicating secure handling of sensitive information.
  • Metadata: The package shows low effort and could be from an unverified author, but there's no direct evidence of malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 7 test file(s) found

  • Test runner config found: pyproject.toml
  • 7 test file(s) detected (e.g. test_cli.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (8579 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 92 type-annotated function signatures detected in source
○ 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 assignment-generator-sebastian-stigler 
Create a Python-based educational tool named 'AutoAssigner' that leverages the 'assignment-generator-sebastian-stigler' package to automate the creation of personalized homework assignments for students. This tool will significantly reduce the time teachers spend on manually crafting assignments, ensuring each student receives tailored tasks based on their performance and needs. Here’s how you can develop this mini-app:

1. **Setup**: Begin by installing the 'assignment-generator-sebastian-stigler' package using pip. Ensure your development environment supports Python 3.7 or later.
2. **User Interface**: Design a simple, user-friendly interface where teachers can input details such as the subject, class level, and specific topics they wish to cover in the assignments.
3. **Student Data Integration**: Allow teachers to upload a CSV file containing student names and their recent assessment scores. Use this data to personalize the difficulty levels of the assignments for each student.
4. **Assignment Generation**: Utilize the core functionalities of the 'assignment-generator-sebastian-stigler' package to generate unique assignments for each student based on their performance. Assignments should include a mix of question types (multiple-choice, short answer, etc.) to cater to different learning styles.
5. **Review and Edit**: Provide a feature where teachers can review the generated assignments, make necessary edits, and add personalized notes or feedback for each student.
6. **Export Options**: Enable teachers to export the finalized assignments in PDF format, ensuring they are formatted neatly and ready for printing or digital distribution.
7. **Analytics Dashboard**: Include an analytics dashboard that shows the distribution of questions across topics, average difficulty levels, and other insightful metrics to help teachers assess the effectiveness of the assignments.
8. **Security Measures**: Implement basic security measures to protect student data and ensure privacy compliance.

By following these steps, you'll create a powerful yet accessible tool that enhances the efficiency of homework assignment creation, making the process more personalized and effective for both educators and students.

💬 Discussion Feed

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