🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no clear signs of malicious activity based on network, shell, obfuscation, and credential risks. However, the metadata risk score indicates potential issues related to the package's newness and lack of community engagement, which raises suspicion.

Metadata risk score of 4 out of 10 due to new package creation and low metadata quality.
Lack of detailed documentation and community interaction could suggest potential supply-chain risks.

Per-check LLM notes

Network: The use of asynchronous HTTP requests is common in many legitimate applications and may not indicate malicious intent.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package appears to be newly created with minimal activity and low metadata quality, raising some suspicion but not definitive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

) async with httpx.AsyncClient(timeout=30) as client: try:
name) async with httpx.AsyncClient(timeout=httpx.Timeout(connect=30, read=120, write=30, pool=3

✓ 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

Only one version has ever been released — brand new package
Author "AG-UI Contributors" 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 ag_ui_watsonx

Create a user-friendly web-based mini-app that integrates IBM WatsonX Orchestrate Agents with AG-UI using the 'ag_ui_watsonx' Python package. This application will serve as a bridge between AG-UI and IBM's powerful AI capabilities, allowing users to easily interact with and manage their WatsonX agents through a simple interface.

Step 1: Set up your development environment by installing the necessary packages including 'ag_ui_watsonx'. Make sure you have the required API keys and authentication details from IBM WatsonX to connect your app to the WatsonX services.

Step 2: Design the UI layout of the application using AG-UI components provided by the 'ag_ui_watsonx' package. Ensure the design is intuitive and easy to navigate, incorporating elements like buttons, forms, and data display areas.

Step 3: Implement the core functionality of the application which includes:
- User Authentication: Allow users to sign in securely using their IBM credentials.
- Agent Management: Provide options to create, edit, delete, and view details of WatsonX agents.
- Task Orchestration: Enable users to define and execute workflows involving multiple agents seamlessly.

Step 4: Enhance the application with additional features such as real-time monitoring of agent activities, alert notifications for critical events, and comprehensive reporting on agent performance.

Step 5: Test the application thoroughly under various scenarios to ensure robustness and reliability. Pay special attention to error handling and security measures.

By following these steps, you'll develop a valuable tool that leverages the power of IBM WatsonX Orchestrate Agents while providing an accessible and efficient user experience.