aigility

v0.1.3 suspicious
4.0
Medium Risk

A modern Python ADK - Agent Development Kit for building AI agents with LangGraph and LangChain. This library provides a comprehensive, type-safe framework for developing intelligent agents with chat, workflow, memory, and knowledge management capabilities.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in terms of obfuscation and credential harvesting. However, the incomplete maintainer profile and potential inactivity raise concerns about its reliability and the possibility of being a supply-chain attack.

  • Low obfuscation risk
  • Low credential risk
  • Incomplete maintainer profile
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of credential theft.
  • Metadata: The maintainer has an incomplete profile and seems to be new or inactive, raising some concerns but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (5.6/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://aigility.readthedocs.io
  • Detailed PyPI description (3339 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

  • 145 type-annotated function signatures detected in source
✦ High Multiple Contributors 8.0

Active multi-contributor project

  • 4 unique contributor(s) across 38 commits in AIGility-Cloud-Innovation/aigility
  • Small but multi-author team (3–4 contributors)

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • e: self._client = httpx.AsyncClient( base_url=self.base_url, tim
✓ 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

Email domain looks legitimate: aigility.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository AIGility-Cloud-Innovation/aigility 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 aigility 
Create a fully-functional mini-application named 'AIAssistant' using the 'aigility' package. This application will serve as a personal AI assistant capable of handling tasks such as scheduling meetings, setting reminders, answering questions based on user input, and managing a user's daily to-do list. The AIAssistant should also have the ability to learn from previous interactions to improve its responses over time.

Steps to follow:
1. Initialize your project environment by installing necessary dependencies including 'aigility'.
2. Design the architecture of the AI agent using 'aigility', focusing on integrating LangGraph and LangChain functionalities for enhanced intelligence.
3. Implement core functionalities like task management (adding, viewing, and deleting tasks), scheduling meetings, and setting reminders.
4. Incorporate a natural language processing system that allows users to interact with the AI Assistant through text-based commands.
5. Develop a learning mechanism within the AI Assistant that enables it to remember past interactions and use this information to refine future responses.
6. Ensure the AI Assistant has access to a knowledge base or external sources to answer general questions posed by the user.
7. Test the application thoroughly to ensure all components work seamlessly together and the AI Assistant performs its tasks accurately.
8. Document your code and provide clear instructions on how to run the AI Assistant application.

Features to include:
- Task Management: Users should be able to add, view, and delete tasks from their to-do list.
- Scheduling: Ability to schedule meetings with specific dates and times.
- Reminders: Set reminders for specific events or tasks.
- Natural Language Processing: Interact with the AI Assistant through text-based commands.
- Learning Mechanism: The AI Assistant should learn from past interactions to improve its responses.
- Knowledge Base Access: Access to a knowledge base or external sources for answering general questions.

Utilize 'aigility' to streamline the development process, leveraging its comprehensive framework for chat, workflow, memory, and knowledge management capabilities.

💬 Discussion Feed

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