jeromeetienne/resumejson_cli — explained in plain English
Analysis updated 2026-05-18
Convert an existing PDF resume into structured JSON that can be edited or reused.
Get a numerical score of how well a resume will perform against ATS filtering software.
Automatically rewrite a resume based on an AI generated review of its weaknesses.
Chain conversion and ATS commands into one scripted end-to-end resume pipeline.
| jeromeetienne/resumejson_cli | 0xradioac7iv/tempfs | 7vignesh/pgpulse | |
|---|---|---|---|
| Stars | 0 | 0 | 0 |
| Language | TypeScript | TypeScript | TypeScript |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 2/5 | 3/5 | 4/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Node.js 20+ and an OpenAI API key for every AI backed command.
resumejson_cli is a command line tool that converts resumes between PDF, JSON, and Markdown formats, and runs an AI powered pipeline to score and improve how well a resume performs against Applicant Tracking Systems, the automated software many companies use to filter job applications. At the center of the tool is a structured JSON format for resumes, checked against a fixed schema. Every command either reads or writes this JSON, so the output of one step can feed directly into the next, or be inspected and edited by hand along the way. The from_pdf command extracts this structured data out of an existing PDF resume using a vision model that reads the rendered pages, while to_pdf and to_markdown render the JSON back into a formatted PDF or Markdown file. The ATS pipeline adds several more commands on top of format conversion. ats_score gives a numerical readiness score you can use to compare before and after versions. ats_review produces a written review covering strengths, weaknesses, and suggestions. ats_question generates the kind of screening questions a recruiter's software might ask, ats_answering drafts answers to them using the resume as context, and ats_optimize rewrites the resume guided by the review. A documented full pipeline chains all of these steps together, from PDF ingestion through to a final optimized PDF and Markdown export. The tool also ships a SKILL.md file that can be installed into an AI agent's skill folder, letting an agent like Claude drive the CLI directly. Running the AI backed commands requires Node.js 20 or newer and an OpenAI API key set as an environment variable, since these commands call OpenAI's models by default. This project is aimed at developers or job seekers comfortable with a command line who want a scriptable way to check and improve a resume's ATS friendliness. It is released under the ISC license.
A command line tool that converts resumes between PDF, JSON, and Markdown, and uses AI to score and rewrite them for better ATS performance.
Mainly TypeScript. The stack also includes TypeScript, Node.js, OpenAI API.
Use freely for any purpose, including commercial use, with minimal restrictions and no warranty.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
double-check against the repo, no cap.