Systemic Resonance Alignment

Code-documentation semantic alignment compares Python AST tokens against Markdown governance terms using cosine similarity. It detects semantic drift between implementation behavior and documented governance text, triggering warnings when mismatches occur.

Run resonance_scanner.py targeting a Python file and its corresponding Markdown document to calculate cosine similarity. Iteratively refactor the code or documentation until the resonance score reaches at least 75.0.

Yes, directed scanning supports directory-wide pairing between .py files and .md counterparts. The scanner automatically matches Python files with their corresponding Markdown documents to calculate semantic alignment.

The minimum resonance score required is 75.0. You must iteratively refactor the Python implementation or Markdown governance text until the cosine similarity score reaches or exceeds this threshold.

No external NLP libraries are required. The scanner uses Python's built-in ast module for token extraction and the math module for cosine similarity calculation, relying only on standard library dependencies.

Use AST token comparison during structural refactors, documentation overhauls, or governance-driven development. It automates semantic drift detection when manual review cannot reliably validate alignment between Python behavior and Markdown governance text.