AI Analysis
The package shows low risks across all categories except for metadata, where incomplete author information suggests potential inexperience or inactivity. However, there are no clear signs of malicious intent.
- No network calls
- No shell execution
- No obfuscation
- Incomplete author information
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution patterns detected, indicating no direct system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer's author information is incomplete and may indicate a less experienced or potentially inactive developer.
Package Quality Overall: Medium (5.0/10)
Test suite present — 2 test file(s) found
Test runner config found: pyproject.toml2 test file(s) detected (e.g. test_routes.py)
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
18 type-annotated function signatures detected in source
Active multi-contributor project
3 unique contributor(s) across 100 commits in anip-protocol/anipSmall but multi-author team (3–4 contributors)
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
Email domain looks legitimate: anip.dev>
All external links appear legitimate
Repository anip-protocol/anip appears legitimate
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
Create a fully-functional mini-application using the 'anip-fastapi' package that serves as a RESTful API for managing a simple inventory system. This application should allow users to add new items, update existing items, delete items, and retrieve item information based on specific criteria. Each item in the inventory should have attributes such as name, description, quantity, and price. The application should be designed with the following key features: 1. User authentication and authorization to ensure only authorized users can perform CRUD operations. 2. Support for filtering items based on various attributes like name, category, and price range. 3. Integration with a database to persistently store inventory data. 4. Logging of all API requests and responses for auditing purposes. 5. Error handling to provide meaningful error messages to clients when operations fail. To achieve these requirements, you will utilize the 'anip-fastapi' package to mount an ANIPService as HTTP routes, enabling you to define and manage your API endpoints efficiently. Additionally, you'll need to incorporate other necessary Python libraries such as FastAPI, SQLAlchemy for database interaction, and Pydantic for data validation. Your task is to outline the steps needed to set up the environment, define the API endpoints, implement the business logic, and test the application to ensure it meets the specified requirements.