argentor

v1.4.0 safe
3.0
Low Risk

Python SDK for the Argentor AI agent framework

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal signs of potential risks with no indications of malicious behavior. The network communication is likely legitimate given its purpose as an SDK for an AI framework.

  • Low network risk due to expected external resource fetching.
  • No evidence of shell execution, obfuscation, or credential mishandling.
Per-check LLM notes
  • Network: The use of an HTTP client suggests network communication which could be legitimate if the package is designed to fetch external resources.
  • Shell: No shell execution patterns detected.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
  • Metadata: The maintainer has only one package, which could indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (5.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • 1 test file(s) detected (e.g. test_core.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://github.com/fboiero/Argentor#readme
  • Detailed PyPI description (2245 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

  • 23 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in fboiero/Argentor
  • Single author but highly active (100 commits)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • ] = tools async with httpx.AsyncClient(timeout=120.0) as client: resp = await client.po
✓ 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

Repository fboiero/Argentor appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Argentor 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 argentor 
Create a personal task management application using the Argentor AI agent framework via its Python SDK, 'argentor'. This application will serve as a digital assistant for users to manage their daily tasks, appointments, and reminders. It will leverage AI capabilities to intelligently organize tasks based on priority and deadlines, suggest optimal times for task completion, and even provide notifications and alerts when important tasks are due.

Key Features:
- Task creation and management with details such as title, description, due date, and priority level.
- Intelligent task organization using the AI agents from Argentor to prioritize tasks based on urgency and importance.
- Notification system to remind users of upcoming tasks and deadlines through email or SMS.
- Integration with calendar applications to sync task deadlines and appointments.
- User-friendly interface for adding, editing, and deleting tasks.

How to Use Argentor Package:
- Utilize the 'argentor' package to initialize and configure the AI agents for task prioritization and scheduling.
- Implement task-related operations (create, read, update, delete) and integrate them with the AI agents for enhanced functionality.
- Integrate notification systems using Argentor's capabilities to ensure timely alerts and reminders.
- Ensure seamless user interaction by providing clear instructions and feedback within the application.

💬 Discussion Feed

Leave a comment

No discussion yet. Be the first to share your thoughts!