🤖 AI Analysis

Final verdict: SUSPICIOUS

The package is flagged as suspicious primarily due to its metadata, including newness, lack of maintainer history, and missing author information. Despite showing low risks in network, shell, obfuscation, and credential areas, the metadata concerns raise suspicion about potential supply-chain attacks.

High metadata risk score
Lack of maintainer history and author information

Per-check LLM notes

Network: The presence of network calls is expected if the package relies on external services or APIs, but further investigation into the URL and purpose is recommended.
Shell: No shell execution patterns detected, which is normal and indicates no immediate risk from this aspect.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
Credentials: No credential harvesting patterns detected, indicating low risk of malicious activities aimed at stealing secrets.
Metadata: The package is suspicious due to its newness, lack of maintainer history, and missing author information.

📦 Package Quality Overall: Low (3.8/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

1 test file(s) detected (e.g. test_skills.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (4786 chars)

○ 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

35 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 score 1.5

Found 1 network call pattern(s)

ttings self._client = httpx.Client( base_url=settings.base_url, verify=

✓ 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: gmail.com>

✓ 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

Only one version has ever been released — brand new package
Author name is missing or very short
Author "" appears to have only 1 package on PyPI (new or inactive account)

✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with aranda-skills

Create a fully functional mini-application called 'SkillMaster' using the Python package 'aranda-skills'. This application will serve as a user-friendly interface to interact with various skills provided by Aranda ASMS's API. SkillMaster should allow users to discover, manage, and utilize different skills available through the Aranda ASMS platform.

Step-by-Step Guide:
1. **Setup**: Install necessary packages including 'aranda-skills' and any other dependencies required for your application. Ensure you have the correct API keys and credentials to authenticate with Aranda ASMS.
2. **Discovery Module**: Implement a feature where users can search for specific skills based on keywords, categories, or tags. Use 'aranda-skills' to fetch relevant skill data from the API.
3. **Management Panel**: Develop a management panel within the application where users can view their current subscriptions to different skills. Users should also be able to subscribe/unsubscribe from skills directly through this panel using 'aranda-skills'.
4. **Interactive Usage**: Allow users to invoke specific skills they have subscribed to. For example, if a user subscribes to a 'weather forecast' skill, they should be able to request weather updates through the application, which would then use 'aranda-skills' to call the appropriate API endpoints.
5. **Customization Options**: Provide customization options where users can adjust settings related to each skill (e.g., preferred units of measurement for weather forecasts).
6. **User Feedback System**: Integrate a simple feedback system allowing users to rate and provide comments on the skills they use. This feedback could be sent back to the Aranda ASMS platform via 'aranda-skills'.
7. **Documentation and Help**: Include comprehensive documentation within the application explaining how to use different features and how to integrate additional skills provided by Aranda ASMS.

Suggested Features:
- Integration with voice commands for hands-free interaction with skills.
- A recommendation engine suggesting skills based on user behavior and preferences.
- Multi-language support to cater to a global audience.
- Detailed analytics dashboard showing usage patterns and skill performance metrics.

How to Utilize 'aranda-skills':
- Use 'aranda-skills' to make authenticated requests to the Aranda ASMS API.
- Leverage the package's methods for searching, subscribing/unsubscribing, invoking skills, and providing feedback.
- Explore the package's documentation to understand how to handle responses and errors effectively.