agentkit-sdk-python

v0.5.9 suspicious
4.0
Medium Risk

Python SDK for transforming any AI agent into a production-ready application. Framework-agnostic primitives for runtime, memory, authentication, and tools with volcengine-managed infrastructure.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risk in terms of network usage, shell execution, and code obfuscation. However, it lacks an associated GitHub repository and has incomplete author information, which raises concerns about its origin and maintainers.

  • No network calls detected
  • Incomplete author information
  • No associated GitHub repository
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires network functionality.
  • Shell: No shell execution detected, indicating no immediate risk of unauthorized command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The package has no associated GitHub repository and the author information is incomplete, 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: gmail.com>

✓ 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 agentkit-sdk-python 
Create a conversational AI assistant named 'TaskMaster' using the 'agentkit-sdk-python' package. TaskMaster will be designed to help users manage their daily tasks efficiently by providing reminders, setting up new tasks, and tracking completed tasks. Here’s how you can build it step-by-step:

1. **Setup Project Environment**: Initialize a new Python project and install the necessary dependencies including 'agentkit-sdk-python'. Ensure your environment is set up correctly to use the SDK.

2. **Define Core Functionality**: Use the 'agentkit-sdk-python' to define the core functionalities of TaskMaster. This includes setting up runtime, managing user memory (storing and retrieving task lists), and handling user authentication.

3. **Implement Task Management Features**: Integrate features such as adding new tasks, marking tasks as completed, and removing tasks from the list. Each task should have details like title, description, due date, and priority level.

4. **Add Reminder System**: Implement a reminder system where TaskMaster sends notifications to users based on the due dates of their tasks. Notifications can be via email, SMS, or within the application itself.

5. **User Authentication**: Utilize the SDK’s authentication primitives to ensure only authenticated users can access and modify their task lists. This ensures data privacy and security.

6. **Integrate Volcengine Infrastructure**: Leverage the managed infrastructure provided by Volcengine to host TaskMaster. This includes setting up cloud services for hosting the backend, ensuring scalability and reliability.

7. **Testing & Deployment**: Thoroughly test TaskMaster to ensure all functionalities work as expected. Once tested, deploy the application using the SDK's deployment capabilities or through Volcengine's managed services.

Suggested Features:
- Voice Input/Output: Allow users to interact with TaskMaster using voice commands.
- Integration with Calendar Apps: Sync tasks with popular calendar applications like Google Calendar.
- Analytics Dashboard: Provide a dashboard for users to view analytics on their task completion rates and productivity.

Utilize the 'agentkit-sdk-python' package throughout the development process to streamline the creation of TaskMaster, focusing on its framework-agnostic nature to ensure flexibility and ease of integration.