🤖 AI Analysis

Final verdict: SUSPICIOUS

The package has moderate network interaction and low maintainer activity, which raises concerns about its legitimacy and potential for unauthorized data transfer.

Moderate network risk
Low maintainer activity

Per-check LLM notes

Network: The presence of network calls suggests the package interacts with external services, which is common but requires scrutiny to ensure no unauthorized data transfer occurs.
Shell: No shell execution patterns were detected, indicating minimal risk of direct system command execution.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of low maintainer activity and poor metadata quality, raising concerns about its legitimacy and purpose.

📦 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_smoke.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (1310 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

8 type-annotated function signatures (partial)

○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

GitHub API error: 404

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

er {API_KEY}" async with httpx.AsyncClient(timeout=timeout_sec) as client: response = await cli

✓ 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 score 3.0

Repository not found (deleted or private)

Repository not found (deleted or private)

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

Author "agentpromocode" 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 agentpromocode-mcp

Create a mini-application named 'PromoCodeResolver' using the Python package 'agentpromocode-mcp'. This application will serve as a tool for resolving promo codes from various online platforms and providing immediate feedback on their validity and benefits. Here’s a step-by-step guide on how to build it:

1. **Setup Environment**: Ensure you have Python installed and create a virtual environment. Install the 'agentpromocode-mcp' package along with any other necessary dependencies.
2. **Design Database Schema**: Plan a simple database schema to store promo codes, their status (valid/invalid), and additional information like expiration dates and benefits.
3. **API Integration**: Use 'agentpromocode-mcp' to integrate with the API services of different websites that offer promo codes. This integration should allow fetching and validating promo codes.
4. **User Interface**: Develop a basic command-line interface (CLI) where users can input promo codes they wish to check. The CLI should also display real-time feedback about each code's status.
5. **Feedback Mechanism**: Implement a feature that allows users to rate the usefulness of valid promo codes. This feedback should be stored in your database for future reference.
6. **Reporting Tool**: Create a reporting tool within the application that generates weekly reports on the most useful and frequently used promo codes.
7. **Security Measures**: Since this application deals with promo codes, ensure that proper security measures are in place, such as encryption for storing sensitive data.

Utilize 'agentpromocode-mcp' to handle the heavy lifting of connecting to external APIs and managing the resolution and feedback processes. This package should streamline the development process significantly, allowing you to focus more on enhancing user experience and integrating additional features.