🤖 AI Analysis

Final verdict: SAFE

The package shows minimal signs of potential misuse, with low risks in both network and shell activities. It appears to be a straightforward SDK without significant red flags.

Low network risk (3/10) with benign-looking operations.
No shell execution detected.

Per-check LLM notes

Network: The observed network calls are likely intended for version checking or similar benign operations, but should be reviewed to ensure compliance with expected behavior.
Shell: No shell execution patterns were detected, indicating low risk for direct system command execution.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

_version self._http = httpx.AsyncClient( base_url=base_url.rstrip("/"), time
ersion self._client = httpx.Client( base_url=base_url.rstrip("/"), time

✓ 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 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 agentflow-client

Your task is to develop a fully-functional mini-application using the 'agentflow-client' Python package, which acts as a bridge to the powerful AgentFlow API designed for orchestrating complex workflows and automations. This mini-app will serve as a personal workflow manager where users can define, manage, and execute their own custom workflows.

### Project Overview:
- **Name**: Workflow Orchestrator
- **Purpose**: A user-friendly tool for managing and executing personalized workflows.

### Core Features:
1. **Workflow Definition**
- Users can define workflows by specifying tasks and the order in which they should be executed.
2. **Task Execution**
- The app will use the 'agentflow-client' to submit workflows for execution.
3. **Status Tracking**
- Provide real-time status updates on each task within a workflow.
4. **Error Handling**
- Implement mechanisms to handle errors gracefully and provide notifications to users when tasks fail.
5. **User Interface**
- Develop a simple web-based UI using Flask or Django for defining workflows and tracking their progress.

### Steps to Build the Application:
1. **Setup Environment**
- Install Python and necessary libraries including 'agentflow-client'.
2. **Define Workflow Models**
- Create classes or models to represent workflows and individual tasks.
3. **Integrate 'agentflow-client'**
- Use 'agentflow-client' to connect to the AgentFlow API and submit workflows for execution.
4. **Build the User Interface**
- Design a basic web interface using Flask/Django where users can input workflow details and monitor progress.
5. **Implement Status Updates**
- Fetch status updates from the AgentFlow API periodically to update the UI.
6. **Add Error Handling**
- Implement error handling logic to catch and notify users of any issues during workflow execution.
7. **Testing and Deployment**
- Thoroughly test the application and deploy it to a cloud service like Heroku or AWS.

### Utilizing 'agentflow-client':
- The 'agentflow-client' package will primarily be used for interacting with the AgentFlow API. It will enable you to submit workflows for execution, retrieve statuses, and manage any other aspects of workflow management supported by the API.

This project will not only demonstrate the power of the 'agentflow-client' but also provide a practical solution for managing personal or business workflows.