atomic-agents

v2.8.0 suspicious
4.0
Medium Risk

A versatile framework for creating and managing intelligent agents.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate obfuscation, which could be used to conceal malicious activities, and the maintainer's metadata is incomplete, raising some suspicion.

  • Moderate obfuscation risk
  • Incomplete maintainer metadata
Per-check LLM notes
  • Network: No network calls detected, which is normal if the package does not require internet access.
  • Shell: No shell execution detected, indicating the package does not execute external commands.
  • Obfuscation: The observed patterns suggest potential obfuscation techniques that could be used to hide code logic, posing a moderate risk.
  • Credentials: No clear evidence of credential harvesting is present based on the provided snippets.
  • Metadata: The maintainer has a new or inactive account and lacks a proper author name, raising some suspicion but not definitive evidence of malice.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 11 test file(s) found

  • 11 test file(s) detected (e.g. test_atomic_agent.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (20405 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 135 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 11 unique contributor(s) across 100 commits in BrainBlend-AI/atomic-agents
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

⚠ Code Obfuscation score 6.0

Found 3 obfuscation pattern(s)

  • " * (ln - 1) + "pass" exec(compile(code, file_path, "exec"), {}) def test__fetch_tool_defini
  • ln - 1) + "pass" exec(compile(code, file_path, "exec"), {}) def test__fetch_tool_definitions_service_branch(mo
  • plit(".", 1) module = __import__(module_name, fromlist=[class_name]) return getattr(module, class_name) def _proces
✓ 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

Repository BrainBlend-AI/atomic-agents appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • 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 atomic-agents 
Create a personalized task management assistant using the 'atomic-agents' package. This application will serve as a digital personal assistant, helping users manage their daily tasks efficiently. The app should allow users to input tasks, set reminders, and receive suggestions on task prioritization based on urgency and importance. Additionally, it should include features like task categorization, progress tracking, and integration with calendar apps for scheduling tasks.

Step 1: Initialize the project and install 'atomic-agents'.
Step 2: Define an agent class that inherits from 'atomic-agents', which will handle user interactions and task management.
Step 3: Implement methods for adding tasks, setting reminders, and categorizing tasks within the agent class.
Step 4: Develop a feature where the agent analyzes the inputted tasks to suggest priority levels based on predefined criteria.
Step 5: Integrate the ability to track the progress of each task and update accordingly.
Step 6: Extend functionality to integrate with popular calendar applications like Google Calendar or Apple Calendar for scheduling tasks.
Step 7: Test the application thoroughly to ensure all functionalities work as expected and refine the user interaction experience.

Utilize 'atomic-agents' to create an intelligent, conversational interface for interacting with the task management system. Ensure that the agent is capable of understanding natural language inputs and providing contextually relevant outputs.

💬 Discussion Feed

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