Smart Resume Screening Project Documentation

Aranya Dutta • 29 April 2026

Resume Processing & Interview Automation System

Overview

This system automates the hiring workflow — from resume upload to interview scheduling.

A candidate uploads a resume through a web app. The system:

Stores the file in Google Drive
Extracts and analyzes content using AI
Scores the candidate based on job requirements
Updates application status
Assigns interview slots (if qualified)
Sends email notifications to candidate and admin

Everything runs inside Google Apps Script and Google Sheets — no external backend required.

Workflow

Candidate uploads resume
Entry created in Google Sheets
Job added to processing queue
Trigger starts processing
Resume is analyzed and scored
Status is updated
Interview slot assigned (if eligible)
Emails are sent

Scoring System

Instead of relying on a single AI score, the system uses a structured rubric:

Skills Match — 40%
Work Experience — 30%
Job Description Fit — 20%
Resume Structure — 10%

Final score is calculated using a formula in code, ensuring consistency and avoiding unreliable AI outputs.

Key Modules & Functions

`00_Config.gs`

Stores system configuration (API keys, thresholds)
Provides helper utilities (UUID, timestamps)

`01_DriveSetup.gs`

Creates and validates required Google Drive folders

`02_SheetHelpers.gs`

Handles sheet creation and data operations (read/write/update)

`03_Logging.gs`

Logs system activity
Sends admin alerts on failures

`04_WebApp.gs`

Serves frontend UI
Handles incoming HTTP requests

`05_UploadHandler.gs`

Validates uploaded files
Saves resumes to Drive
Creates application entry
Adds job to queue

`06_QueueProcessor.gs`

Processes queued jobs
Implements retry logic
Runs via time trigger

`07_TextExtraction.gs`

Converts PDF/DOCX/TXT into plain text

`08_Sanitizer.gs`

Detects prompt injection attempts
Cleans and validates resume text

`09_AIExtraction.gs`

Sends data to Groq API
Extracts structured candidate data
Validates AI response

`10_ResumeProcessor.gs`

Main pipeline controller
Executes full processing flow

`11_SlotAllocator.gs`

Assigns interview slots
Uses locking to prevent conflicts

`12_EmailSender.gs`

Sends candidate emails
Sends admin notifications

`13_Setup.gs`

One-click setup
Creates sheets, folders, triggers
Adds custom menu

Triggers

onChange Trigger — instant processing on new entry
Time-based Trigger (2 min) — backup processing system

Application Status

UPLOADED — Submitted
PROCESSING — Under evaluation
DONE — Selected and scheduled
WAITLIST — Qualified but no slots
REVIEW — Flagged for issues
ERROR — Failed after retries

Key Features

Fully automated hiring pipeline
AI-powered resume analysis
No server required (Google ecosystem)
Secure API handling
Retry and logging system
Automated interview scheduling

Problems Faced & Solutions

1. Learning Google Apps Script

I initially had no experience with Apps Script, coming from a Python backend background.
Understanding execution flow, triggers, and debugging in this environment took significant effort.

2. AI Scoring Issues (Groq API)

The AI initially returned rounded and unreliable scores.

Solution:

Broke scoring into multiple categories
Let AI provide sub-scores instead of final score
Implemented a mathematical scoring layer in code
Ensured consistent and accurate evaluation

3. Prompt Injection via Resume

Candidates attempted to manipulate the system by inserting hidden instructions inside resumes.

Solution:

Built a sanitization layer
Scans resumes for prompt injection patterns
Flags suspicious resumes for review
Applies penalties to maintain fairness

4. Concurrency & Trigger Conflicts

Multiple triggers could process the same job simultaneously, causing inconsistencies.

Solution:

Implemented LockService-based job queue
Ensures only one process handles a job at a time
Prevents race conditions and data corruption

Future Plans

1. Anonymous Candidate Ranking

Show candidates their rank among applicants
No personal data revealed
Improves transparency

2. Detailed Feedback Emails

Provide personalized improvement suggestions
Include:
- Skill gaps
- Experience feedback
- Resume improvements

Tech Stack

Google Apps Script
Google Sheets
Google Drive
Groq API (Llama3-70b)

Summary

This system demonstrates how a fully automated hiring pipeline can be built without traditional backend infrastructure, combining cloud tools, AI, and workflow automation.