🤖 AI Analysis

Final verdict: SAFE

The package shows no signs of malicious activity such as network calls, shell executions, or credential harvesting. However, the metadata risk score is elevated due to the maintainer's new or inactive account.

No network calls or shell executions detected
Maintainer has a new or inactive account

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires network interactions for its functionality.
Shell: No shell execution patterns detected, indicating no direct system command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
Metadata: The maintainer has a new or inactive account and lacks detailed author information, raising some suspicion but not conclusive evidence of malice.

🔬 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

Email domain looks legitimate: lahman.dev>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository jmelahman/agentic-kanban appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author name is missing or very short
Author "" 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 agentic-kanban

Develop a task management application called 'AI Agent Hub' that leverages the 'agentic-kanban' package to manage AI agent sessions efficiently. This application will allow users to create and manage multiple kanban boards for different projects, each board representing a unique workflow where AI agents can be assigned tasks.

The application should include the following core functionalities:
1. User Authentication: Users must be able to register and log in to their accounts securely.
2. Kanban Board Creation: Users can create multiple kanban boards for different projects. Each board should have columns like 'To Do', 'In Progress', and 'Done'.
3. Task Management: Users can add tasks to any column on the board, drag and drop tasks between columns to reflect changes in status, and delete tasks if necessary.
4. AI Agent Integration: Tasks can be assigned to AI agents which are managed through the 'agentic-kanban' package. The package allows tracking the session of each AI agent working on tasks.
5. Real-time Updates: Ensure that updates made to any board are reflected in real-time across all connected devices.
6. Reporting: Provide analytics and reports on the progress of tasks and the efficiency of AI agents.
7. Collaboration: Allow multiple users to work on the same board simultaneously, with permissions control over who can edit and view the board.

To utilize the 'agentic-kanban' package effectively, follow these steps:
1. Initialize a new kanban board using the package's API.
2. For each task added to the board, use the package to initiate an AI agent session if the task requires AI assistance.
3. Monitor the session status of each AI agent through the package to track progress and completion of tasks.
4. Integrate the package's feedback mechanism to update task statuses automatically as AI agents complete their assigned tasks.

Ensure your application is user-friendly, responsive, and scalable. Use modern web technologies and design principles to make it visually appealing and easy to navigate.