🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of network activity, shell execution, code obfuscation, or credential harvesting, indicating it poses minimal risk.

No network calls
No shell executions
No obfuscation
No credential harvesting

Per-check LLM notes

Network: No network calls detected, which is normal if the package does not require external communications.
Shell: No shell executions detected, indicating the package does not attempt to run external commands.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.

📦 Package Quality Overall: Medium (5.4/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

Test runner config found: pyproject.toml

◈ Medium Documentation 7.0

Some documentation present

Documentation URL: "Documentation" -> https://github.com/0xzerolight/anki_miner/blob/main/README.m
Detailed PyPI description (13879 chars)

○ Low Contributing Guide 4.0

No contributing guide or governance files found

Development Status classifier >= Beta

◈ Medium Type Annotations 5.0

Partial type annotation coverage

192 type-annotated function signatures detected in source

◈ Medium Multiple Contributors 5.0

Limited contributor diversity

1 unique contributor(s) across 100 commits in 0xzerolight/anki_miner
Single author but highly active (100 commits)

🔬 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

Repository 0xzerolight/anki_miner appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

Author "Anki Miner Contributors" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with anki-miner

Your task is to develop a mini-application that leverages the 'anki-miner' package to create a personalized Japanese vocabulary learning tool. This tool will automate the process of extracting useful Japanese words and phrases from anime subtitles and then integrate them into Anki flashcards for memorization. Here’s a detailed breakdown of the project steps and suggested features:

1. **Anime Subtitle Mining**: Utilize the 'anki-miner' package to automatically scrape and mine Japanese vocabulary from popular anime series subtitles. Ensure that the mining process includes filtering out common words, focusing on unique and contextually rich terms.
2. **Word Frequency Analysis**: Implement a feature within your application to analyze the frequency of mined words across different episodes or seasons. This analysis will help in prioritizing the creation of flashcards based on word usage.
3. **Anki Integration**: Use 'anki-miner' to directly export the mined vocabulary into Anki flashcards. Each flashcard should include the Japanese word, its pronunciation, English translation, and example sentences where applicable.
4. **User Interface**: Develop a simple yet intuitive GUI using Python libraries such as Tkinter or PyQt, allowing users to select which anime series they want to mine vocabulary from and view their progress.
5. **Customization Options**: Allow users to customize their learning experience by setting preferences like difficulty level, number of new words per day, and preferred study methods (e.g., spaced repetition).
6. **Progress Tracking**: Incorporate functionality to track user progress over time, including statistics on the number of words learned, correct answers, and review intervals.
7. **Data Export**: Provide an option for users to export their Anki decks in a format compatible with other platforms, ensuring they can continue their learning journey beyond the application.

By following these steps and incorporating these features, you will create a powerful tool that not only enhances language learning but also makes the process enjoyable and efficient.