🤖 AI Analysis

Final verdict: SAFE

The package shows low risk across all categories with no signs of malicious activity. However, it has low maintenance and metadata quality which might affect its reliability.

No network calls or shell executions detected
Low maintenance and metadata quality

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external communication for its functionality.
Shell: No shell execution patterns detected, indicating no immediate risk of unauthorized command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: Package shows low maintenance and metadata quality, but lacks clear indicators of malicious intent.

📦 Package Quality Overall: Low (4.4/10)

✦ High Test Suite 9.0

Test suite present — 11 test file(s) found

Test runner config found: conftest.py
Test runner config found: pyproject.toml
11 test file(s) detected (e.g. conftest.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (2274 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

71 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 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

Email domain looks legitimate: outlook.com>

✓ 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 agentstate-lib

Your task is to develop a collaborative note-taking application using the 'agentstate-lib' Python package. This application will allow multiple users to simultaneously edit and manage notes in real-time, ensuring consistency and coherence across all changes made by different users. The application will feature user authentication, real-time collaboration, conflict resolution, and version control. Here’s a detailed plan on how to implement it:

1. **Setup Environment**: Start by setting up your development environment with Python, Flask (for web framework), and 'agentstate-lib'. Install the necessary packages using pip.
2. **User Authentication**: Implement a simple user authentication system where users can sign up and log in. Use JWT for secure token-based authentication.
3. **Note Creation & Editing**: Allow authenticated users to create and edit notes. Each note should have a unique identifier, title, content, and timestamps for creation and last update.
4. **Real-Time Collaboration**: Utilize 'agentstate-lib' to handle state management and synchronization of notes among multiple users. Ensure that each user's actions (e.g., editing text) are immediately reflected in the view of other collaborators.
5. **Conflict Resolution**: Implement a mechanism to resolve conflicts when two or more users try to edit the same part of a note simultaneously. This could involve showing a diff of changes or merging edits based on timestamps.
6. **Version Control**: Keep track of different versions of a note as it gets edited over time. Users should be able to revert to previous versions if needed.
7. **Testing**: Write unit tests and integration tests to ensure all components work together seamlessly. Focus on testing the collaboration and conflict resolution features thoroughly.
8. **Documentation**: Document your code well, explaining how 'agentstate-lib' is integrated into the application and how it contributes to the functionality of real-time collaboration.

Use 'agentstate-lib' to manage the states of notes and users, enabling efficient and consistent real-time updates across all connected clients. This will be crucial for the seamless collaboration experience you aim to provide.