AI Analysis
Final verdict: SUSPICIOUS
The package exhibits low risks for obfuscation and credential theft, but its metadata is lacking and suggests a lack of effort or transparency from the developer, which raises suspicion.
- Metadata risk is relatively high at 6/10.
- Lack of description and other metadata.
Per-check LLM notes
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows several low-effort indicators and lacks important metadata, raising suspicion but not definitive proof of malice.
Package Quality Overall: Low (3.6/10)
✦ High
Test Suite
9.0
Test suite present — 3 test file(s) found
3 test file(s) detected (e.g. test_answerer.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
4 type-annotated function signatures (partial)
○ 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
No author email provided
Suspicious Page Links
All external links appear legitimate
Git Repository History
No GitHub repository linked
No GitHub repository link found
Maintainer History
score 8.0
4 maintainer concern(s) found
Only one version has ever been released — brand new packageAuthor name is missing or very shortAuthor "" 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 ask-my-docs
Create a document-based question answering system using the Python package 'ask-my-docs'. This application will allow users to upload multiple documents (PDFs, Word Docs, etc.) and then ask questions about the content of those documents. The system should be able to extract relevant information from the uploaded documents and provide accurate answers to user queries. Steps to follow: 1. Set up a basic Flask web application framework to handle file uploads and form submissions. 2. Integrate the 'ask-my-docs' package to process and index the uploaded documents. 3. Implement a feature to enable users to input their questions via a simple web interface. 4. Use the indexed data from 'ask-my-docs' to generate responses to user queries. 5. Display the answers on the web interface in a clean and readable format. Suggested Features: - Support for various document formats including PDF, DOCX, TXT, etc. - A search history feature that stores past queries and answers for easy reference. - An option for users to flag incorrect or irrelevant answers for improvement. - Integration with a feedback loop to improve the accuracy of future answers based on user interactions. - Basic authentication to limit access to authorized users only.
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