Resume Relevance Scoring Automation

I need an end-to-end n8n workflow that watches a “Resumes” folder in Google Drive, pulls each incoming PDF, runs OCR to capture the text, and compares it against a single Job Description PDF stored in a separate Drive folder.

The flow should then:
• parse out the candidate’s name, mobile, and email from the resume text,
• apply a keyword-matching algorithm to generate a relevance score on a 0-100 scale, and
• write a new line (or update an existing one) in a Google Sheet with the candidate data, the Drive file link, the numeric score, and a short, human-readable explanation of why that score was assigned (e.g., matched skills, missing requirements).

Updates must trigger automatically whenever new resumes land in the folder, so the sheet is always current without manual intervention.

Deliverables:
1. An importable n8n workflow (.json) with clear node naming.
2. Any helper scripts or functions used for OCR or keyword logic (JavaScript preferred inside n8n Code nodes).
3. A brief README showing how to connect the Google Drive and Google Sheets credentials and how to tweak keyword weights if needed.

Acceptance criteria: the workflow processes at least five sample PDFs end-to-end, populates the sheet in under five minutes per file, and produces explanations that reference the actual matched or missing keywords.