🤖 AI Analysis

Final verdict: SAFE

The package has low individual risk scores across all categories except for metadata, where it shows signs of low maintainer activity. However, there is no concrete evidence of malicious intent or supply-chain attack.

No network calls detected
No shell execution patterns
No obfuscation patterns
Low credential risk

Per-check LLM notes

Network: No network calls detected, which is normal unless the package requires external services.
Shell: No shell execution patterns detected, indicating no direct system command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, indicating safe handling of secrets and credentials.
Metadata: The package shows signs of low maintainer activity and metadata quality, which could indicate potential risks but does not conclusively point to malice.

📦 Package Quality Overall: Low (1.2/10)

○ Low Test Suite 1.0

No test suite detected

No test files or test-runner configuration detected

○ 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

○ Low Type Annotations 1.0

No type annotations detected

No type annotations, py.typed marker, or stub files detected

○ 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 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" 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 ai-interior-design-info

Create a modern interior design recommendation app using the 'ai-interior-design-info' package. This app will allow users to input their room dimensions, desired style, and color preferences to receive personalized design suggestions. Here's a step-by-step guide on how to develop this app:

1. **Setup**: Install necessary packages including 'ai-interior-design-info'. Note that since the package description states it is retired, you'll need to simulate its functionality based on typical AI-driven interior design tools.
2. **User Interface Design**: Develop a user-friendly interface where users can input their room dimensions (length, width, height), select a preferred style (e.g., minimalist, traditional, modern), and choose their favorite colors.
3. **Data Input Handling**: Create functions to process user inputs and store them temporarily for further use.
4. **Design Recommendations Generation**: Utilize simulated 'ai-interior-design-info' functionalities to generate design recommendations based on user inputs. This could include furniture placement, color schemes, and decorative items.
5. **Visualization**: Implement a feature that allows users to visualize their room designs in 3D or 2D views, showcasing how the recommended designs would look in real life.
6. **Save & Share Options**: Enable users to save their designs or share them via social media platforms.
7. **Feedback Loop**: Incorporate a feedback system where users can rate their satisfaction with the design suggestions, helping improve future recommendations.

Ensure your application is responsive and accessible across different devices. Additionally, consider integrating external APIs for more detailed information about specific furniture pieces or decor items.