AI Analysis
The package exhibits low activity and poor metadata quality, which raises some suspicion. However, there is no clear indication of malicious intent from the other checks.
- Low maintainer activity
- Poor metadata quality
Per-check LLM notes
- Network: The observed network call patterns are typical for packages that interact with external services, but further investigation is needed to confirm legitimacy.
- Shell: No shell execution patterns were detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising some suspicion but not conclusive evidence of malice.
Package Quality Overall: Low (2.0/10)
No test suite detected
No test files or test-runner configuration detected
No documentation detected
No documentation URL, doc files, or meaningful description found
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
27 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Found 4 network call pattern(s)
est(task) async with httpx.AsyncClient(timeout=self._timeout) as client: response = awached_card async with httpx.AsyncClient(timeout=self._timeout) as client: resp = await c} async with httpx.AsyncClient(timeout=self._timeout) as client: try:uest(task) async with httpx.AsyncClient() as client: response = await client.request(
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)Package has no PyPI classifiers (low effort / metadata quality)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a mini-application called 'Agent Passport Manager' using Python that leverages the 'agentpassport-adapters' package. This tool will serve as a bridge between different types of agent passport services, allowing users to interact with MCP and REST-based agent passport systems seamlessly. The application should have the following core functionalities: 1. **User Interface**: Develop a simple yet intuitive command-line interface (CLI) for users to interact with the application. 2. **Service Discovery**: Implement a feature that allows users to discover available agent passport services. This could include listing all known MCP and REST-based services that the user has access to. 3. **Service Interaction**: Enable users to perform actions on discovered services, such as querying agent details, updating agent statuses, and managing agent permissions. 4. **Configuration Management**: Provide a way for users to configure the application with necessary credentials and settings required to communicate with the agent passport services. 5. **Logging and Monitoring**: Integrate logging capabilities to track user interactions and service responses, aiding in troubleshooting and monitoring. 6. **Security Measures**: Ensure that sensitive information, like API keys and passwords, are handled securely within the application. To achieve these functionalities, you'll need to utilize the 'agentpassport-adapters' package effectively. For instance, use its MCP and REST adapters to handle communication protocols appropriately. Additionally, consider implementing error handling and providing informative messages to guide users through their interactions with the application.
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