🤖 AI Analysis

Final verdict: SAFE

The package exhibits legitimate behavior with no signs of malicious intent or harmful actions. However, the low maintainer activity and poor metadata quality raise minor concerns.

No signs of malicious activity detected.
Low maintainer activity and poor metadata quality noted.

Per-check LLM notes

Network: The observed network call pattern suggests legitimate HTTP requests for card resolution, which could be part of the package's functionality.
Shell: No shell execution patterns detected.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows low maintainer activity and poor metadata quality, raising some concerns but not strong evidence of malintent.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

eak.Literal ): async with httpx.AsyncClient() as httpx_client: resolver = A2ACardResolver(

✓ 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: imt-atlantique.fr>

✓ 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 a2a-agentspeak

Create a fully-functional mini-application that simulates a simple negotiation scenario between two parties using the 'a2a-agentspeak' package in Python. This application will showcase the use of AgentSpeak agents communicating via the A2A/ACL protocol to negotiate the sale of an item. Here’s a step-by-step guide to building this application:

1. **Define the Scenario**: Set up a scenario where one agent acts as a seller offering an item for sale, while another agent acts as a buyer interested in purchasing the item.

2. **Agent Creation**: Use the 'a2a-agentspeak' package to create two distinct AgentSpeak agents - one for the seller and one for the buyer. Each agent should have its own set of beliefs, goals, and actions tailored to their role in the negotiation process.

3. **Communication Protocol**: Implement communication between these agents through the A2A/ACL protocol provided by 'a2a-agentspeak'. Ensure that messages exchanged include offers, counteroffers, acceptances, and rejections.

4. **Negotiation Logic**: Develop the negotiation logic within each agent, allowing them to make decisions based on the current state of the negotiation. For example, the seller might lower the price if no agreement is reached after a certain number of rounds, and the buyer might increase their offer if the initial price is too high.

5. **Simulation Interface**: Create a simple user interface or command-line interface to start and monitor the negotiation process. Users should be able to initiate negotiations, view the current state of the negotiation, and see the outcome once a deal is made or the negotiation fails.

6. **Logging and Reporting**: Implement logging to track all messages exchanged during the negotiation process. Additionally, provide a summary report at the end of the negotiation detailing the final terms agreed upon, if any, and the overall duration of the negotiation.

7. **Testing and Validation**: Test your application thoroughly to ensure that it handles various negotiation scenarios effectively, including successful negotiations, failed negotiations due to disagreement, and situations where negotiations break down.

8. **Enhancements and Customization**: Consider adding additional features such as multiple buyers or sellers, varying negotiation strategies, or even integrating external factors like time constraints or changing market conditions into the negotiation process.

By following these steps, you will create a comprehensive mini-application that leverages the capabilities of the 'a2a-agentspeak' package to simulate real-world negotiation dynamics.