AI Analysis
Final verdict: SUSPICIOUS
The package has low risks in terms of network usage, shell execution, and code obfuscation. However, the metadata risk score is high due to the package's newness and limited contributor activity, raising suspicions about its legitimacy.
- High metadata risk due to new package creation and limited activity
- Single contributor adds uncertainty about the package's origin and intentions
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package's functionality requires external communication.
- Shell: No shell executions detected, indicating the package does not attempt to execute system commands without user interaction.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows signs of being newly created with minimal activity and a single contributor, raising concerns about its legitimacy.
Package Quality Overall: Low (3.8/10)
✦ High
Test Suite
9.0
Test suite present — 1 test file(s) found
Test runner config found: pyproject.toml1 test file(s) detected (e.g. test_cli.py)
○ Low
Documentation
1.0
No documentation detected
No documentation URL, doc files, or meaningful description found
○ 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
5 type-annotated function signatures (partial)
○ Low
Multiple Contributors
2.0
Single-author or unverifiable project
1 unique contributor(s) across 2 commits in agentculture/antigravitydSingle author with few commits — possibly a personal or throwaway project
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
score 5.0
Git history flags: Very few commits: 2 total
Very few commits: 2 totalSingle contributor with only 2 commit(s) — possibly throwaway account
Maintainer History
score 4.0
2 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor "AgentCulture" 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 antigravityd
Create a mini-application called 'GravityGuard' using the Python package 'antigravityd'. This application will serve as a lightweight tool for managing delegated tasks and reviewing pull requests within a GitHub repository. Here's a step-by-step guide on how to build it: 1. **Project Setup**: Start by setting up your development environment. Ensure you have Python installed and create a virtual environment for your project. Install 'antigravityd' via pip. 2. **Configuration**: Create a configuration file where users can specify their GitHub credentials and the repositories they want to manage. 3. **Task Delegation**: Implement functionality that allows users to delegate specific tasks to other contributors in their repository. Use 'antigravityd' to handle the background processing of these tasks. 4. **Pull Request Review**: Integrate a feature that fetches open pull requests from specified repositories and provides an interface for users to review them. Utilize 'antigravityd' to monitor and notify users about updates or changes in the PR status. 5. **Notifications**: Set up a notification system that alerts users about task completions or changes in PR statuses. 'antigravityd' should be leveraged to ensure these notifications are handled efficiently without blocking the main application thread. 6. **User Interface**: Develop a simple command-line interface (CLI) for interacting with GravityGuard. Users should be able to easily view, delegate, and review tasks and PRs through this CLI. 7. **Testing**: Write tests for each feature of GravityGuard to ensure reliability and robustness. 8. **Documentation**: Provide comprehensive documentation detailing how to install, configure, and use GravityGuard effectively. Suggested Features: - Ability to assign multiple tasks to a single contributor - Option to set deadlines for delegated tasks - Integration with webhooks for real-time PR status updates - Support for multi-repository management - Detailed logs for all actions performed within GravityGuard By following these steps and incorporating the suggested features, you'll create a powerful yet easy-to-use tool for managing tasks and reviewing PRs in GitHub repositories.
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