🤖 AI Analysis

Final verdict: SAFE

The package appears safe with low risk scores across all categories except for metadata, where it shows signs of low maintenance and quality issues. However, there is no evidence of malicious activities.

Low network, shell, obfuscation, and credential risks.
Metadata quality and maintenance concerns.

Per-check LLM notes

Network: The network calls suggest the package is making API requests, which could be normal if it's designed to interact with external services.
Shell: No shell execution patterns were detected.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows low maintenance and metadata quality indicators which could suggest potential risks.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 4.5

Found 3 network call pattern(s)

ncode("utf-8") request = urllib.request.Request( api_url, data=body, head
) try: with urllib.request.urlopen(request, timeout=8) as response: data =
client = self.http_client or httpx.AsyncClient(timeout=self.config.timeout_seconds) try:

✓ 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 ad-creative-intelligence-mcp

Create a fully-functional mini-application called 'AdCreativeDesigner' using the Python package 'ad-creative-intelligence-mcp'. This application will serve as a tool for marketers and advertisers to generate creative content ideas for their advertising campaigns. Here are the steps and features you need to implement:

1. **User Interface Setup**: Develop a simple yet intuitive command-line interface (CLI) for users to interact with the application. The CLI should guide users through the process of inputting necessary information and viewing the output.

2. **Input Parameters**: Allow users to specify key details about their target audience, campaign goals, budget constraints, and preferred media channels (e.g., social media platforms like Facebook, Instagram).

3. **Content Idea Generation**: Utilize the 'ad-creative-intelligence-mcp' package to generate unique and relevant content ideas based on the user inputs. These ideas could include themes, slogans, visuals, and even preliminary copywriting suggestions.

4. **Media Channel Optimization**: Provide recommendations on which media channels would be most effective for each piece of content based on the user's specified preferences and the generated content ideas.

5. **Output Presentation**: Present the generated content ideas and channel recommendations in a clear, organized manner. Users should be able to easily review and save these suggestions for further development.

6. **Feedback Loop**: Implement a feature where users can provide feedback on the generated ideas, allowing the application to refine its suggestions over time.

7. **Integration with External Tools**: Optionally, integrate the application with external tools such as stock photo services or graphic design software to allow for immediate visual concept creation based on the generated ideas.

The 'ad-creative-intelligence-mcp' package will be crucial in processing user inputs and generating creative content ideas. Ensure that your implementation leverages the package's capabilities to offer value-added insights and recommendations.