academic-agent-toolkit

v0.1.3 suspicious
4.0
Medium Risk

Plug-and-play CLI for academic research agent skills and Paper Search MCP setup

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows a moderate risk level due to its high shell risk score, which suggests potential for executing unauthorized commands. However, there are no indications of obfuscation, credential harvesting, or malicious intent.

  • High shell risk (7/10)
  • No evidence of obfuscation or credential harvesting
Per-check LLM notes
  • Network: Network calls to PyPI are common for fetching package metadata and updates, but direct network calls might indicate unexpected behavior.
  • Shell: Executing shell commands can be risky if not properly sanitized or controlled, suggesting potential for unauthorized actions.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, which could indicate a new or less active account, but no other suspicious activities were flagged.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 3.0

Found 2 network call pattern(s)

  • uest try: resp = urllib.request.urlopen("https://pypi.org/pypi/academic-agent-toolkit/json",
  • th) -> None: try: urllib.request.urlretrieve(url, archive) except urllib.error.URLError a
✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

  • cess try: return subprocess.run(cmd, capture_output=True, text=True).stdout except Excep
  • port subprocess result = subprocess.run(upgrade_cmd.split(), capture_output=False) if result.ret
✓ 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

Repository JhonHander/academic-agent-toolkit appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Academic Agent Toolkit contributors" 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 academic-agent-toolkit 
Create a Python-based academic research assistant application named 'ResearchMate' using the 'academic-agent-toolkit' package. This tool aims to streamline the process of searching, organizing, and managing academic papers for researchers. Here are the steps and features you need to implement:

1. **Setup**: Begin by installing the 'academic-agent-toolkit' package and setting up a basic CLI interface for user interaction.
2. **Paper Search**: Implement a feature that allows users to search for academic papers based on keywords, authors, publication dates, and journals. Use the 'academic-agent-toolkit' to handle the backend processes and integrate with academic databases.
3. **Organizer**: Develop an organizer function where users can categorize and tag their found papers for easy retrieval later. This could include creating folders, applying tags, and even adding notes.
4. **Notification System**: Integrate a notification system that alerts users about new publications related to their interests. This can use the 'academic-agent-toolkit' to monitor specific topics and notify users via email or in-app messages.
5. **User Interface**: Design a simple yet effective UI for the CLI to enhance user experience. Ensure commands are intuitive and provide clear feedback.
6. **Export Functionality**: Allow users to export their organized papers and notes into various formats like PDFs, CSVs, or JSON files for further analysis or sharing.
7. **Integration with External Tools**: Consider integrating ResearchMate with other tools commonly used in academia such as Zotero or Mendeley for seamless data transfer.

The 'academic-agent-toolkit' package will be central to handling the complex tasks behind the scenes, such as interfacing with academic databases, processing large datasets, and managing user interactions efficiently. Your goal is to create a robust, user-friendly application that significantly aids in the daily workflow of academic researchers.