autogen

v0.13.3 safe
2.0
Low Risk

Alias package for ag2

🤖 AI Analysis

Final verdict: SAFE

The package shows minimal risk indicators with no signs of malicious activity. The low scores across all categories suggest that the package is likely safe.

  • Low network, shell, obfuscation, and credential risks.
  • Metadata suggests a single-package maintainer, possibly indicating a new or less active account.
Per-check LLM notes
  • Network: The observed network calls seem to be related to fetching plain text and images, which could be part of legitimate functionality like content scraping or downloading resources.
  • Shell: No shell execution patterns were detected.
  • 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 (6.2/10)

✦ High Test Suite 9.0

Test suite present — 14 test file(s) found

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

Some documentation present

  • Detailed PyPI description (18476 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

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

Active multi-contributor project

  • 23 unique contributor(s) across 100 commits in ag2ai/ag2
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

  • lain-text file response = requests.get(PLAIN_TEXT_URL) response.raise_for_status() expected
  • ompute its md5 response = requests.get(IMAGE_URL, stream=True) response.raise_for_status()
  • BeautifulSoup response = requests.get(url) soup = BeautifulSoup(response.text, "html.parser")
  • autifulSoup response = requests.get(url) soup = BeautifulSoup(response.text, "html.parser
  • t BeautifulSoup response = requests.get(url) soup = BeautifulSoup(response.text, "html.parser")
✓ 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: ag2.ai

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository ag2ai/ag2 appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Chi Wang & Qingyun Wu" 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 autogen 
Create a command-line tool named 'AutoScripter' using the Python package 'autogen', which is an alias for 'ag2'. This tool will help developers automatically generate boilerplate code for common programming tasks based on user input. The tool should have the following functionalities:

1. **Setup**: Upon running the tool, it should prompt the user to choose between different programming languages (e.g., Python, JavaScript, Java).
2. **Generate Boilerplate Code**: Based on the selected language, the tool should ask the user to specify the type of code they need (e.g., class definition, function creation, loop structures). It then generates the corresponding boilerplate code.
3. **Customization Options**: Provide options for customization such as adding docstrings/comments, specifying variable names, and adjusting indentation styles.
4. **Output Options**: Allow the user to either view the generated code directly in the console or save it to a file.
5. **Help and Documentation**: Include a help command that explains each feature and provides examples.

The 'autogen' package will be utilized to automate the generation process of boilerplate code, making the tool more efficient and capable of handling complex requests with less manual intervention. Your task is to design the structure of this tool, implement its core functionalities, and ensure it's user-friendly and easy to extend with new language support.

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