ai-launcher

v0.4.1 safe
4.0
Medium Risk

Universal AI CLI launcher with local context management for multi-project environments

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators and does not engage in network activities, which are common red flags for malicious behavior. However, the potential for shell command execution without proper validation warrants closer monitoring.

  • Shell risk due to potential unvalidated shell command execution
  • Low activity level of the maintainer's account
Per-check LLM notes
  • Network: No network calls were detected, which is typical for benign packages.
  • Shell: Shell execution commands without proper input validation or output handling could pose a risk if used to execute arbitrary commands.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer has only one package, suggesting a potentially new or less active account.

📦 Package Quality Overall: Medium (5.4/10)

✦ High Test Suite 9.0

Test suite present — 20 test file(s) found

  • Test runner config found: pyproject.toml
  • 20 test file(s) detected (e.g. test_aider_provider.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (5889 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

  • 127 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 35 commits in solentlabs/ai-launcher
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • try: result = subprocess.run( [command, "--version"], cap
  • ider try: subprocess.run(cmd, check=True) # nosec B603, B607 except FileNotF
  • ect_path) ... subprocess.run(["myai"], check=True) ... ... def cleanu
  • aude try: subprocess.run(["claude"], check=True) # nosec B603, B607 except F
  • result = subprocess.run( ["claude", "--version"],
  • ilot try: subprocess.run(["copilot"], check=True) # nosec B603, B607 except
✓ 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 solentlabs/ai-launcher appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Solent Labs™" 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 ai-launcher 
Create a command-line interface (CLI) tool named 'AIProjectManager' using the Python package 'ai-launcher'. This tool will serve as a personal AI project manager, allowing users to manage multiple AI projects within different contexts easily. The project manager should support the following functionalities:

1. **Project Initialization**: Users should be able to initialize new AI projects with pre-defined configurations. Each project should have its own directory structure and initial setup files (e.g., README.md, requirements.txt).
2. **Context Switching**: Implement context switching to allow seamless navigation between different AI projects. This feature ensures that the environment variables and settings are correctly managed for each project.
3. **Dependency Management**: Provide an easy way to install dependencies for each project. This includes managing virtual environments and installing necessary packages from the requirements.txt file.
4. **Interactive Shell Access**: Offer an interactive shell access where users can run Python code snippets directly related to their current project context.
5. **Logging and Monitoring**: Include logging capabilities to track project activities such as initialization, dependency installation, and context switches. Additionally, provide basic monitoring of project health based on logs.
6. **Help and Documentation**: Ensure that the tool provides comprehensive help documentation accessible via the CLI. This documentation should include examples and best practices for using the tool effectively.

To achieve these functionalities, you will heavily rely on the 'ai-launcher' package for managing local contexts, initializing projects, and handling dependencies. The 'ai-launcher' package simplifies the process of setting up and maintaining multiple AI projects by providing a universal CLI interface and advanced context management features. Your task is to design and implement 'AIProjectManager' to showcase the versatility and power of the 'ai-launcher' package in a real-world application.