Step 2: Connect Google Drive for CV Storage and Retrieval

Store the uploaded CV and then download it for text extraction.

1. In Store CV in Drive, set Name to ={{ $json['Upload CV'] }} and Input Data Field Name to Upload_CV.
2. Choose the target Google Drive folder by setting Folder ID to your folder (replace [YOUR_ID]).
3. Credential Required: Connect your googleDriveOAuth2Api credentials in Store CV in Drive.
4. In Retrieve CV File, set Operation to download and File ID to ={{ $json.id }}.
5. Credential Required: Connect your googleDriveOAuth2Api credentials in Retrieve CV File.

Step 3: Extract and Assemble CV + Form Data

Convert the PDF CV to text and merge it with form data into a unified payload.

1. In Extract Resume Text, set Operation to pdf to extract text from the downloaded CV.
2. In Combine Form and CV, set Mode to combine and Combine By to combineAll.
3. In Assemble Comparison Payload, keep the provided JavaScript to output candidate_name, email_address, skills_claimed, job_history_claimed, and cv_actual_content.

Extract Resume Text outputs into Combine Form and CV, which then outputs to Assemble Comparison Payload.

Step 4: Set Up AI Evaluation and Parsing

Send the assembled data to the AI evaluator, then parse and format the results.

1. In AI Evaluation & Scoring, keep Prompt Type as define and use the provided prompt text, which references {{ $json.candidate_name }}, {{ $json.email_address }}, {{ $json.skills_claimed }}, {{ $json.job_history_claimed }}, and {{ $json.cv_actual_content }}.
2. Ensure Gemini Chat Model is connected as the language model for AI Evaluation & Scoring.
3. Credential Required: Connect your googlePalmApi credentials in Gemini Chat Model (AI credentials are added to the model node, not the agent).
4. In Parse AI Output, keep the JavaScript that extracts JSON from the AI response.
5. In Format Score Summary, keep the JavaScript that maps fields to Candidate, Answer Quality, CV Match, Fit Summary, and Final Score.

Step 5: Configure Google Sheets Output and Ranking

Append scores to the sheet, then re-rank all rows by final score.

1. In Append Score to Sheet, set Operation to append, Document ID to your sheet (replace [YOUR_ID]), and Sheet Name to Sheet1.
2. Map the columns exactly as configured: candidate_name, email_address, Answers Quality, CV match, Fit Summary, and Final Score using the provided expressions like ={{ $json['Final Score'] }} and ={{ $('Assemble Comparison Payload').item.json.email_address }}.
3. Credential Required: Connect your googleSheetsOAuth2Api credentials in Append Score to Sheet.
4. In Fetch Sheet Rows, select the same Document ID and Sheet Name to retrieve all rows after appending.
5. Credential Required: Connect your googleSheetsOAuth2Api credentials in Fetch Sheet Rows.
6. In Order by Score, keep the JavaScript that sorts by final_score descending.
7. In Reset Sheet Data, set Operation to clear to wipe existing rows before writing the ranked data.
8. Credential Required: Connect your googleSheetsOAuth2Api credentials in Reset Sheet Data and Write Ranked Rows.

Append Score to Sheet outputs to Fetch Sheet Rows, then Order by Score outputs to Reset Sheet Data, which outputs to Write Ranked Rows.

Step 6: Test and Activate Your Workflow

Run a full test with a sample CV to validate the end-to-end scoring and ranking.

1. Click Execute Workflow and submit the Form Intake Trigger with a PDF CV.
2. Confirm that Store CV in Drive uploads the file and Retrieve CV File downloads it successfully.
3. Check that AI Evaluation & Scoring returns JSON, Parse AI Output extracts scores, and Append Score to Sheet adds a new row.
4. Verify that Write Ranked Rows rewrites the sheet in descending score order.
5. Once successful, toggle the workflow to Active for production use.