AI Analysis
The package shows no signs of malicious activity or external risks, with low scores across all assessed categories. The metadata risk is slightly elevated due to sparse author information.
- No network calls detected
- No shell execution detected
- No obfuscation or credential harvesting detected
- Sparse author information
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external API interactions.
- Shell: No shell execution patterns detected, indicating the package likely does not execute external commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The author information is sparse, suggesting potential lack of transparency.
Package Quality Overall: Low (3.8/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Detailed PyPI description (16642 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Active multi-contributor project
6 unique contributor(s) across 100 commits in americanphilosophicalsociety/aspace-wb-scriptsActive community — 5 or more distinct 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: amphilsoc.org>
All external links appear legitimate
Repository americanphilosophicalsociety/aspace-wb-scripts 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 mini-application that helps APS staff efficiently prepare CSV files for ingestion into Islandora 8 using Workbench. Your task is to design a user-friendly tool that simplifies the process of generating these CSV files from Archival Resource Key (ARK) identifiers provided by the ArchivesSpace database. The application should have the following core functionalities: 1. **ARK Identifier Input**: Allow users to input multiple ARK identifiers at once or through a file upload. 2. **CSV File Generation**: Use the 'aspace-wb-scripts' package to generate the necessary CSV files based on the input ARK identifiers. Ensure the CSV format aligns with the requirements for ingestion into Islandora 8 via Workbench. 3. **Preview Functionality**: Provide a preview of the CSV content before finalizing the generation process to allow users to review and make any necessary adjustments. 4. **Error Handling**: Implement robust error handling to manage issues such as invalid ARK identifiers or missing data, providing clear feedback to the user. 5. **Logging and Reporting**: Include logging capabilities to track the generation process and report any errors encountered during execution. 6. **User Interface**: Develop a simple and intuitive web-based interface using Python's Flask framework to interact with the backend functionality. The UI should guide users through the process with clear instructions and visual feedback. The 'aspace-wb-scripts' package will be crucial in automating the conversion of ARK identifiers into the appropriate CSV structure required by Islandora 8. Your goal is to streamline this process, reducing manual effort and minimizing errors in the preparation of archival material for digital preservation.
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