AI Analysis
The package shows very low risk across all categories with no network calls, shell executions, or obfuscation techniques observed. The only slight concern is the maintainer's limited package history.
- No network calls
- No shell execution
- No obfuscation patterns
- Maintainer has only one package
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution detected, indicating no immediate risk of unauthorized system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which might indicate a new or less active account, but there are no other red flags.
Package Quality Overall: Low (3.8/10)
Partial test coverage signals detected
1 test file(s) detected (e.g. test_metadata_manager.py)
Some documentation present
Detailed PyPI description (2266 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
12 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
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
No GitHub repository linked
No GitHub repository link found
1 maintainer concern(s) found
Author "Allen Institute for Neural Dynamics" 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 mini-application called 'MetadataMaster' that leverages the Python package 'aind-metadata-manager' to manage metadata for various datasets in a neuroscience research setting. The application should allow users to easily add, update, query, and delete metadata entries for different types of data such as images, videos, and behavioral logs. It should also provide functionalities to validate the integrity of metadata entries based on predefined schemas and ensure consistency across datasets. Key Features: 1. User-friendly command-line interface for interacting with the application. 2. Support for multiple dataset types, each with its own schema for metadata. 3. Ability to import/export metadata in JSON format for easy sharing and backup. 4. Validation checks to ensure all required fields are present and correct before saving metadata. 5. Query functionality to search for specific metadata entries using filters. 6. Integration with a simple database backend (SQLite) for persistent storage of metadata. How to Utilize 'aind-metadata-manager': - Use 'aind-metadata-manager' to define and validate schemas for different types of metadata. - Leverage its capabilities to efficiently handle metadata operations like adding, updating, querying, and deleting entries. - Implement validation logic based on the provided schemas to maintain data integrity. - Explore additional features of 'aind-metadata-manager' to enhance the application's functionality, such as support for versioning or auditing metadata changes. Your task is to design and implement the 'MetadataMaster' application from scratch, ensuring it meets the above requirements and effectively utilizes 'aind-metadata-manager'.