AI Analysis
The package has moderate risk due to its low maintainer activity and poor metadata quality, which could suggest potential neglect or abandonment. However, it shows no signs of malicious intent based on network, shell, obfuscation, and credential risks.
- Low maintainer activity
- Poor metadata quality
Per-check LLM notes
- Network: The network call pattern is expected for a package likely interfacing with VK API over HTTP/HTTPS.
- Shell: No shell execution patterns detected, indicating low risk.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows low maintainer activity and poor metadata quality, which may indicate a lack of community support or maintenance effort.
Package Quality Overall: Low (2.0/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
133 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Found 1 network call pattern(s)
) self._session = aiohttp.ClientSession(timeout=timeout) return self._session async def
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: mail.ru>
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
3 maintainer concern(s) found
Author 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)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a fully functional mini-app using the 'aiovkteams' package in Python. This app will serve as a basic bot for VK Teams, designed to manage tasks and communications within a team. The app should include the following functionalities: 1. **User Authentication**: Implement a secure method for users to authenticate with their VK Teams credentials. 2. **Task Management**: Allow users to create, view, update, and delete tasks directly from the chat interface. 3. **Notification System**: Set up notifications for task deadlines and updates. 4. **Integration with AI**: Utilize the capabilities of another AI service (such as OpenAI's API) to provide suggestions or insights on tasks based on user input. 5. **Reporting Features**: Generate simple reports summarizing completed and pending tasks for the team. To achieve these functionalities, follow these steps: - **Step 1**: Setup your development environment with Python, 'aiovkteams', and any additional libraries you might need. - **Step 2**: Authenticate users using VK Teams API, ensuring data security and privacy. - **Step 3**: Design the task management system where users can interact via commands like '/create', '/view', '/update', and '/delete'. - **Step 4**: Integrate a notification system that sends reminders about upcoming deadlines or changes to tasks. - **Step 5**: Connect to an AI service to enhance the functionality of the bot, providing intelligent responses and suggestions. - **Step 6**: Develop reporting tools that can compile and present task statuses in a clear, understandable format. The 'aiovkteams' package will be central to interacting with VK Teams, handling all communication and command processing. Ensure your application is well-documented and includes error handling to provide a robust user experience.
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