AI Analysis
Final verdict: SAFE
The package shows minimal risk indicators with no network calls, shell executions, obfuscations, or credential risks. The metadata suggests a possibly new or less active maintainer, but this alone does not indicate any malicious intent.
- No network calls detected
- Single package from maintainer
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communication.
- Shell: No shell execution detected, indicating no immediate risk of command injection or unauthorized system access.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, indicating they may be new or less active, but no other red flags are present.
Package Quality Overall: Low (2.4/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (5301 chars)
○ Low
Contributing Guide
4.0
No contributing guide or governance files found
Development Status classifier >= Beta
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
○ Low
Multiple Contributors
1.0
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
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
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 2.0
1 maintainer concern(s) found
Author "Anmol Khandeparkar" 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 agentqa
Create a fully-functional mini-application named 'AgentQA-TestSuite' that leverages the 'agentqa' Python package to simulate and test multi-agent interactions in a chatbot environment. The goal of this application is to identify potential issues such as deadlocks, memory leaks, and role violations before deploying the chatbot into a production setting. Here are the steps and features you should include in your project: 1. **Setup**: Install the necessary packages including 'agentqa' and any other dependencies required for the application. 2. **Design Agents**: Design multiple agents (e.g., UserAgent, AdminAgent, SupportAgent) each with specific roles and functionalities. 3. **Interaction Scenarios**: Define several interaction scenarios where these agents interact with each other in a simulated chat environment. 4. **Testing Framework**: Utilize the 'agentqa' package to set up a testing framework that can automatically run these scenarios, monitor interactions, and report any issues detected. 5. **Report Generation**: Implement a feature within the application that generates detailed reports on the tests conducted, highlighting any issues found during the simulation. 6. **User Interface**: Develop a simple command-line interface (CLI) through which users can select different test scenarios and view test results. 7. **Documentation**: Provide comprehensive documentation detailing how to use the 'AgentQA-TestSuite' application, including setup instructions, usage examples, and an explanation of the output. The 'agentqa' package will be crucial in this project for its ability to manage and analyze the complex interactions between multiple agents, ensuring that all aspects of their behavior are thoroughly tested.