AI Analysis
The package shows minimal risk indicators, with no detected network calls, shell executions, or obfuscation. However, the metadata risk due to limited maintainer history suggests cautious monitoring.
- Low network, shell, and obfuscation risks
- Limited maintainer history
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 no suspicious system command execution.
- Obfuscation: No obfuscation patterns detected, indicating low risk of code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no immediate risk of unauthorized access to secrets.
- Metadata: The package is new with limited maintainer history and no author details provided.
Package Quality Overall: Low (4.8/10)
Test suite present — 2 test file(s) found
Test runner config found: pyproject.toml2 test file(s) detected (e.g. __init__.py)
Some documentation present
2 documentation file(s) (e.g. copyright.py)Brief PyPI description (638 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
48 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
3 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)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Build a simple Python application using the aws_sdk_connecthealth package to demonstrate its core features.
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