AI Analysis
The package shows minimal risk in terms of direct malicious activities such as network calls or shell executions. However, the absence of a repository link and a short author name suggest potential issues with the package's credibility and origin.
- Missing repository link
- Short author name
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 no immediate signs of malicious activity like command injection.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The missing repository and short author name raise concerns, indicating potential low credibility.
Package Quality Overall: Low (2.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (1606 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
58 type-annotated function signatures detected in source
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
No suspicious network call patterns found
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
Repository not found (deleted or private)
Repository not found (deleted or private)
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Your task is to develop a command-line utility using Python that leverages the 'arc-ogchallenge' package to manage and monitor autonomous agents deployed in the oil and gas industry. This utility will allow users to interact with the ARC API to perform various operations such as deploying new agents, retrieving status updates, and managing configurations. Hereβs a detailed breakdown of the steps and features your utility should include: 1. **Setup and Installation**: Ensure that the utility is easily installable via pip and includes a setup.py file for distribution. 2. **Authentication**: Implement a secure way to authenticate users with the ARC API using OAuth2 or similar protocol. 3. **Agent Management**: - Deploy new agents into specific environments. - Retrieve details about existing agents including their current state, performance metrics, and logs. - Update configurations of existing agents. - Terminate agents when no longer needed. 4. **Monitoring**: - Provide real-time monitoring of agent performance through a CLI interface. - Generate periodic reports summarizing the performance of all agents over a specified time period. 5. **Configuration**: - Allow users to set up default configurations for new deployments. - Support customization of these configurations based on user preferences or specific operational requirements. 6. **Help and Documentation**: - Include comprehensive help documentation accessible via the CLI. - Provide examples of common tasks and workflows. The 'arc-ogchallenge' package will be central to your application, serving as the interface between your utility and the ARC API. It will handle all communication with the API, making it easier for you to focus on implementing the above features. Your goal is to create a robust, user-friendly tool that simplifies the management and monitoring of autonomous agents in the oil and gas industry.
π¬ Discussion Feed
No discussion yet. Be the first to share your thoughts!
Report Abuse / Security Issue