agentmesh-message-bus

v3.7.0 safe
3.0
Low Risk

A lightweight, broker-agnostic message bus designed specifically for AI Agents

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no network calls, shell executions, obfuscations, or credential risks detected. The metadata risk slightly increases suspicion due to the author having only one package, but this alone is insufficient to conclude malicious intent.

  • Low risk scores across all categories.
  • Metadata risk due to the author having only one package.
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package's functionality requires external communication.
  • Shell: No shell execution patterns detected, indicating the package does not execute system commands directly.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author has only one package, which may indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (6.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/microsoft/agent-governance-toolkit#readme
  • Detailed PyPI description (7414 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 152 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 14 unique contributor(s) across 100 commits in microsoft/agent-governance-toolkit
  • Active community — 5 or more distinct contributors

🔬 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

Repository microsoft/agent-governance-toolkit appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Microsoft Corporation" 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 agentmesh-message-bus 
Develop a mini-application named 'AgentChat' that facilitates real-time communication between multiple AI agents using the 'agentmesh-message-bus' package. This application will serve as a platform where different AI agents can exchange information, collaborate on tasks, and even engage in simulated conversations. Here’s a detailed plan for building this application:

1. **Setup**: Begin by installing the necessary packages including 'agentmesh-message-bus'. Ensure your development environment is set up correctly for Python.
2. **Design the Architecture**: Design an architecture where each AI agent acts as both a publisher and a subscriber. Use 'agentmesh-message-bus' to handle the messaging between these agents.
3. **Creating Agents**: Implement at least three distinct AI agents within the application. Each agent should have unique capabilities and roles (e.g., one could be responsible for data analysis, another for generating summaries, and a third for handling user interactions).
4. **Message Bus Integration**: Utilize 'agentmesh-message-bus' to integrate these agents into a cohesive system. Configure the message bus to allow agents to publish messages to specific topics and subscribe to relevant topics based on their roles.
5. **Real-Time Communication**: Ensure that the application supports real-time communication. When an agent publishes a message, other subscribed agents should receive it almost instantaneously.
6. **User Interface**: Develop a simple web interface where users can interact with the agents. Users should be able to send messages to specific agents or broadcast messages to all agents.
7. **Logging and Monitoring**: Implement logging for all messages exchanged through the message bus. Additionally, provide a monitoring dashboard within the UI to track the health and activity of each agent.
8. **Testing and Validation**: Thoroughly test the application to ensure reliability and efficiency in message delivery. Validate that all agents can communicate effectively and perform their designated tasks.
9. **Documentation**: Write comprehensive documentation detailing how to install, configure, and use 'AgentChat'. Include examples of how to extend the application with additional agents or functionalities.

By following these steps, you'll create a versatile and powerful mini-application that showcases the capabilities of the 'agentmesh-message-bus' package in facilitating seamless communication between AI agents.