Code Readability Checker
Analyzes code to ensure non-developers (managers, stakeholders, new team members) can understand it.
What It Checks
- Clear naming: No cryptic abbreviations (usr_tkn → userToken)
- Plain comments: Everyday language, not technical jargon
- Documentation: What/Why/How for major sections
- Comment ratio: At least 20% of lines should be comments
Usage
python3 analyze.py --path your-file.py --strictness lenientExample
Bad Code (score: 71/100):
def proc(usr, tkn):
tmp = usr + tkn
return tmp * 2Issues: Cryptic names, no comments, unclear purpose.
Good Code (score: 95/100):
def process_user_authentication(username, auth_token):
"""Validate user credentials and return auth score"""
combined_credential = username + auth_token
return combined_credential * 2Known Issues
- May flag false positives in documentation files
- Works best on actual production code
- Use
--strictness lenientto reduce noise