🤖 AI Analysis

Final verdict: SAFE

The package is considered safe as it does not exhibit any high-risk behaviors such as shell execution or credential harvesting. However, there are minor concerns regarding network security and metadata that suggest low maintenance.

No shell execution or credential harvesting patterns detected.
Potential issues with network security and package maintenance.

Per-check LLM notes

Network: The use of HTTP requests is common for SDKs that interact with external services, but should be reviewed to ensure proper authorization and encryption.
Shell: No shell execution patterns detected, which is expected and safe.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
Credentials: No credential harvesting patterns detected, suggesting legitimate usage without hidden credential theft.
Metadata: The package shows signs of low maintenance and potential lack of transparency, raising some suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

equest.""" async with httpx.AsyncClient(timeout=timeout) as http_client: minimal_card =
H, "") async with httpx.AsyncClient(transport=self.transport, timeout=self.timeout) as client:
.Response: async with httpx.AsyncClient(transport=transport, base_url=base_url) as client:

✓ 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 agentic-layer-sdk-msaf

Create a simple web-based task management system using Python and the 'agentic-layer-sdk-msaf' package. This system should allow users to log in, create tasks, assign them to other users, mark tasks as completed, and view their own task lists. Additionally, implement a feature where users can comment on tasks and receive notifications when there are updates.

### Features:
- User authentication and authorization.
- Task creation and management (add, edit, delete).
- Task assignment between users.
- Marking tasks as completed.
- Commenting on tasks.
- Notifications for task updates.

### Utilization of 'agentic-layer-sdk-msaf':
- Use the package to integrate the task management system with Microsoft's Agent Framework, allowing for seamless interaction with external agents or services through the Agentic Layer SDK. Ensure that all interactions are instrumented and logged appropriately for debugging and monitoring purposes.

### Steps:
1. Set up a basic Flask or FastAPI backend with user authentication.
2. Integrate the 'agentic-layer-sdk-msaf' package to convert your service into an instrumented A2A Starlette web application.
3. Develop endpoints for task CRUD operations (create, read, update, delete).
4. Implement task assignment and completion tracking.
5. Add functionality for comments and notifications.
6. Test thoroughly, ensuring all features work as expected and that the integration with the Microsoft Agent Framework is functioning correctly.
7. Deploy the application to a cloud platform like Heroku or AWS for accessibility.