archon-arch-ai

v0.1.0 suspicious
4.0
Medium Risk

AI-powered project architecture specification generator for agentic development workflows

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows no immediate signs of malicious activity, but the unavailability of its repository and the maintainer's limited history with PyPI raise concerns that warrant further investigation.

  • Repository not found
  • Maintainer has limited PyPI history
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires internet access to function.
  • Shell: No shell execution patterns detected, indicating no immediate risk of command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The repository is not found, and the maintainer has limited history with PyPI, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Medium (5.2/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 5 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 7.0

Some documentation present

  • Detailed PyPI description (4664 chars)
  • Classifier: Documentation
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
  • 31 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Could not retrieve contributor data from GitHub

  • GitHub API error: 404

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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

  • Only one version has ever been released — brand new package
  • Author "Archon 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 archon-arch-ai 
Create a fully-functional mini-application called 'ProjectArchitect' using the Python package 'archon-arch-ai'. This application will serve as an AI-driven tool to assist developers in generating project architectures based on specific requirements and technologies. Here are the steps and features you need to implement:

1. **Setup and Initialization**: Start by installing the necessary packages including 'archon-arch-ai'. Ensure your application has a clean and user-friendly interface where users can input their project details such as technology stack, project type (web app, mobile app, backend service), and any additional specifications.

2. **Input Specification**: Develop a feature within 'ProjectArchitect' that allows users to specify the desired architecture style (e.g., microservices, monolithic, serverless). The application should also provide options for users to select specific frameworks and libraries they prefer to use.

3. **AI Architecture Generation**: Utilize the core functionalities of 'archon-arch-ai' to generate a comprehensive project architecture based on the inputs provided by the user. The generated architecture should include high-level diagrams, directory structures, and a detailed breakdown of components and services.

4. **Customization Options**: Offer customization options within the generated architecture. Users should be able to modify certain aspects of the architecture such as adding or removing components, adjusting configurations, etc.

5. **Export and Integration**: Implement functionality that allows users to export the generated architecture in formats such as PDF, JSON, or YAML. Additionally, provide integration capabilities with popular version control systems like Git to facilitate seamless project setup.

6. **Feedback Loop**: Incorporate a feedback mechanism where users can rate the generated architecture and provide suggestions for improvement. Use this feedback to refine future generations of architectures.

The goal is to create a versatile tool that simplifies the process of setting up new projects by leveraging AI to suggest optimal architectures based on user-defined criteria.

💬 Discussion Feed

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