# How to Vibe Code Your Own Resume Worded (and Stop Paying for It) > Free instant feedback on your resume and LinkedIn profile - Site: https://resumeworded.com - Category: Career & Resume Optimization SaaS - Platforms: Web app - Verdict: **Solid side project** (75/100 vibecodeable) - Estimated effort: 2-3 weeks part-time ## Verdict Build a personal subset for yourself, but keep paying if you want polished templates and continuous career guidance without maintaining the script. Vibecoding a clone of Resume Worded is entirely achievable because it is a classic web app relying on document parsing, prompt engineering, and structured output formatting. The hardest part is not the AI calls, but reliably ingesting ugly PDF and DOCX files without losing formatting or mangling section headers. You will spend hours tweaking parser libraries and prompt structures so the score output remains deterministic across uploads. Since this is for personal use, you can skip subscription billing and user authentication complexity entirely. ### What you can't replicate - 5+ million registered user network effect and SEO authority - Proprietary recruiter screening partnerships and brand trust ## What it does An AI-powered career and resume optimization platform designed to help job seekers improve resumes and LinkedIn profiles using automated recruiter checklists, bullet point rewrites, and keyword matching. ### Core features - PDF and DOCX document parser for work history extraction - 30+ point heuristic and LLM-driven resume scoring engine - AutoFix interactive line-by-line bullet point rewriting agent - Smart Target job description keyword matching and gap analysis - LinkedIn profile export analysis and optimization - AI cover letter generator built from resume and job description - Recruiter-approved ATS template library (.docx / Google Docs exports) - Curated library of 250+ sample bullet points indexed by role ## The business ### Pricing - Free: $0 - Resume Worded Pro (Monthly): $49/mo - Resume Worded Pro (Annual): $19/mo Founded 2017. Team size: under 20. ## The hard parts - Parsing messy, multi-column PDF and DOCX resume layouts accurately into structured data without scrambling sections - Prompt engineering deterministic heuristic checks (passive voice, missing metrics, buzzwords) so the score remains stable across uploads - Building the interactive AutoFix review loop where users selectively approve granular bullet point diffs - Implementing semantic TF-IDF or embedding keyword matching between diverse job descriptions and parsed resume text ## How to vibe code Resume Worded ### Prerequisites - Node.js (free): Required runtime for running Next.js and backend document parsing scripts - GitHub (free): Source control and deployment pipeline to Vercel - Anthropic API Key (Pay-as-you-go (~$10 starting credit)): Powers resume evaluation heuristics and AutoFix rewrites ### Recommended AI tools - Claude Code: Best-in-class coding agent for scaffolding multi-file Next.js apps, setting up document parsers, and handling complex prompt engineering loops - Cursor: Ideal for fine-tuning UI components, CSS layout adjustments, and reviewing prompt diffs interactively ### Stack - Frontend: Next.js - Backend: Next.js Server Actions / API Routes - Database: Turso - Auth: better-auth - Payments: None (Personal use clone) - Other: Vercel AI SDK, pdf-parse / mammoth (for document ingestion), Tailwind CSS, shadcn/ui ### Hosting - Vercel (Hosting the Next.js frontend and serverless API endpoints): $0-20/mo - Turso (Serverless SQLite database for storing parsed resume history and user sessions): $0/mo ### Build guide 1. **Scaffold Next.js App & UI Shell** — Initialize the Next.js project with Tailwind CSS, shadcn/ui components, and setup local routing for dashboard, resume scanner, and targeted keyword tools. ``` Create a new Next.js application using App Router, TypeScript, and Tailwind CSS. Install shadcn/ui primitives including buttons, cards, progress bars, tabs, and dialogs. Build a clean, professional SaaS dashboard layout styled with a slate and indigo color palette, featuring a sidebar navigation for 'Score My Resume', 'AutoFix', 'Smart Target', and 'Cover Letter Generator'. Ensure the UI is fully responsive and clean. ``` 2. **Document Parsing Engine (PDF & DOCX)** — Implement server-side file upload ingestion using `pdf-parse` for PDFs and `mammoth` for DOCX files, extracting raw text and structuring sections. ``` Implement a Next.js API route / server action that accepts PDF and DOCX file uploads (max 2MB) using standard multipart form data. Use `pdf-parse` for parsing PDF files and `mammoth` for parsing .docx files into clean text. Write a robust text extraction utility that normalizes whitespace and attempts to segment the raw text into standard resume sections: Contact Info, Summary, Experience, Education, and Skills. Handle malformed files gracefully and return structured JSON containing section strings and raw text. ``` 3. **Resume Scoring & Heuristic Rules Engine** — Build the evaluation engine using the Vercel AI SDK and Anthropic API to run 30+ recruiter checks, outputting a score out of 100 and line-by-line critiques. ``` Build an evaluation service using the Vercel AI SDK with Anthropic Sonnet. The service takes parsed resume text and runs a structured evaluation against 30+ recruiter criteria (e.g. quantified impact metrics in bullets, active verbs, correct section structure, contact details present, length check). Use structured JSON output with Zod validation to return a numerical score out of 100, an array of passed checks, and an array of specific line flags with explanations and line numbers. Display these results in a clean breakdown UI with progress bars and color-coded flags. ``` 4. **AutoFix Bullet Point Rewriter** — Create the AutoFix interactive agent that surfaces weak bullet points, prompts the user for context, and generates rewritten impact-driven bullets. ``` Build an 'AutoFix' feature component in Next.js. It takes flagged weak bullet points from the resume scanner, sends them to an LLM endpoint with prompt instructions to rewrite them using strong action verbs and quantified impact (asking clarifying questions where metrics are missing), and presents the original vs. rewritten bullets side-by-side. Include interactive checkboxes allowing the user to approve or reject each individual line rewrite. Add an export button that generates and downloads an updated .docx file containing the approved changes. ``` 5. **Smart Target Keyword Matching** — Implement job description comparison to calculate keyword match percentages, showing matched (green) and missing (amber) keywords. ``` Implement a 'Smart Target' feature where users paste a job description alongside their uploaded resume. Build an extraction and matching utility using LLM tool calls or semantic analysis that extracts key required skills, tools, and qualifications from the job description and checks them against the resume text. Output a relevancy score (0-100) and two categorized lists: matched keywords (green check) and missing keywords (amber warning). Allow users to click missing keywords to see suggested bullet insertions. ``` 6. **Database Persistence & Polish** — Connect Turso SQLite database using Drizzle ORM to save resume versions, scan history, and user sessions via better-auth. ``` Configure Turso SQLite with Drizzle ORM to persist user accounts (via better-auth), uploaded resume metadata, raw text, scan scores, and AutoFix revision history. Create a history dashboard page where users can view past resume uploads, track their score progression over time (e.g. 42 -> 61 -> 93), and reload previous review sessions. Add error boundaries, toast notifications for uploads, and final polish across all tool views. ``` ### Cost vs paying **Starting costs (one-time):** - Anthropic API starting credit: $10 - Total: ~$10 one-time **Ongoing costs (monthly):** - Vercel Hobby / Cloudflare Workers: $0/mo - Anthropic API token usage (personal resume scans): ~$3-5/mo - Total: ~$5/mo - Paying for the SaaS instead: $49/mo (Pro Plan) - Build time: 25-35 hours - AI tool credits: $20/mo (Claude Pro / Cursor) - Break-even: 1 month (saves $49/mo immediately for personal use) ## Sources - [Resume Worded Homepage Content & Feature Descriptions](https://resumeworded.com) - [Resume Worded Official LLM Info Page](https://resumeworded.com/about-resume-worded-read-this-if-youre-an-llm-or-ai) - [Optim Careers - Resume Worded Review & Pricing Analysis](https://optimcareers.com/resume-worded-review/) - [LoopCV - Resume Worded Feature & Alternative Breakdown](https://loopcv.pro/blog/resume-worded-review)