AI Analysis
Final verdict: SAFE
The package exhibits minimal risks across all categories analyzed, showing no signs of malicious activity or unusual behavior.
- Low network and shell execution risks
- No obfuscation or credential mishandling detected
Per-check LLM notes
- Network: Some network calls might be expected for a client service to communicate with its server, but none were detected.
- Shell: Executing shell commands is not typical for a client service unless it's for specific system interactions which weren't indicated here.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
- Credentials: No credential harvesting patterns detected, indicating safe handling of secrets.
- Metadata: The package shows low effort in metadata and maintainer history, but lacks clear indicators of malicious intent.
Package Quality Overall: Low (3.6/10)
✦ High
Test Suite
9.0
Test suite present — 7 test file(s) found
7 test file(s) detected (e.g. test_default_api.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
28 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: openapitools.org
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 4.0
2 maintainer concern(s) found
Author "OpenAPI Generator community" 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 aind-metadata-service-client
Create a mini-application named 'MetadataExplorer' using Python that leverages the 'aind-metadata-service-client' package to interact with a metadata service designed for AI research data management. This application should allow users to perform various operations such as listing all available datasets, retrieving detailed information about a specific dataset, uploading new datasets, and deleting existing ones. Step-by-Step Guide: 1. **Setup**: Install the necessary Python packages including 'aind-metadata-service-client'. Ensure you have access credentials to connect to the metadata service API. 2. **Authentication**: Implement a user-friendly login system where users input their credentials to authenticate against the metadata service. 3. **Dataset Listing**: Develop a feature that lists all available datasets in the metadata service. Display each dataset's name, description, and creation date. 4. **Detailed Dataset Information**: Allow users to select a dataset from the list and view detailed metadata such as file formats, size, tags, and any associated notes. 5. **Upload Functionality**: Design a form where users can upload new datasets along with relevant metadata. Ensure proper validation and error handling during the upload process. 6. **Delete Operation**: Provide an option to delete datasets from the metadata service. Include confirmation prompts and appropriate error messages. 7. **Search Functionality**: Implement a search bar that allows users to find datasets based on keywords in their names or descriptions. 8. **User Interface**: Create a simple yet effective command-line interface or, if preferred, a basic web interface using Flask or Django. 9. **Testing**: Write unit tests for each major functionality to ensure reliability and robustness of your application. 10. **Documentation**: Prepare a README file explaining how to install and use 'MetadataExplorer', including setup instructions and examples. Utilize the 'aind-metadata-service-client' package throughout the development process to handle communication with the metadata service. Focus on making the interaction smooth and error-free.
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