automas-notification-koishi

v0.0.4 suspicious
4.0
Medium Risk

Notification Koishi channel

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has low risks in terms of network, shell, and obfuscation activities, but its metadata suggests poor maintenance and quality issues, raising concerns about potential supply-chain risks.

  • Low maintainer activity
  • Poor metadata quality
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access to function properly.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command injection or similar attacks.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious credential theft.
  • Metadata: The package shows signs of low maintainer activity and poor metadata quality, but lacks clear indicators of malicious intent.

📦 Package Quality Overall: Low (2.8/10)

○ 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 (217 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

  • 5 type-annotated function signatures (partial)
○ 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 automas-notification-koishi 
Create a personal task management application called 'TaskMaster' using Python, which integrates with the 'automas-notification-koishi' package for real-time notifications. TaskMaster will allow users to add, edit, delete, and mark tasks as completed. Additionally, it should support setting reminders for upcoming deadlines and sending notifications through Koishi when these deadlines are approaching or have been missed.

Step 1: Design the User Interface
- Develop a simple yet intuitive command-line interface (CLI) for interacting with TaskMaster.
- Ensure that the CLI supports commands like 'add', 'edit', 'delete', 'list', 'mark_complete', and 'set_reminder'.

Step 2: Implement Core Functionality
- Use a SQLite database to store user tasks, including details such as title, description, due date, and completion status.
- Implement logic to handle CRUD operations (Create, Read, Update, Delete) for tasks.

Step 3: Integrate Notification System
- Utilize the 'automas-notification-koishi' package to set up a notification system that triggers reminders based on task deadlines.
- Configure the application to send notifications through Koishi when a task is due or overdue.

Step 4: Enhance User Experience
- Add functionality to categorize tasks into different lists (e.g., Work, Personal).
- Implement sorting options within the CLI to view tasks by category, due date, or priority.

Step 5: Test and Deploy
- Thoroughly test all features of TaskMaster to ensure reliability and usability.
- Consider deploying the application as a Docker container for easy sharing and use by others.

Suggested Features:
- Support for recurring tasks (weekly, monthly).
- Integration with popular calendar apps for synchronization.
- Export task lists to CSV or JSON format.
- Dark mode option for the CLI interface.

How to Utilize 'automas-notification-koishi':
- After adding or editing a task, the application should automatically calculate the time until the deadline.
- If the deadline is less than a predefined threshold (e.g., 24 hours), the application should trigger a notification through Koishi.
- Notifications should include the task title, description, and the remaining time until the deadline.

By following these steps and utilizing the 'automas-notification-koishi' package effectively, you'll create a robust task management tool that keeps users informed about their upcoming deadlines in real-time.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!