resume-json

name

resume-json

description

Convert resumes between PDF, JSON, and Markdown, and optimize them for Applicant Tracking Systems (ATS) using AI. Use this skill whenever the user wants to extract a resume from a PDF, render a resume back to PDF or Markdown, score how ATS-friendly a resume is, generate or answer ATS-style screening questions, or rewrite a resume to improve its ATS performance. Triggers on: "extract resume from PDF", "convert resume to PDF", "convert resume to markdown", "score my resume", "ATS score", "ATS review", "optimize my resume for ATS", "ATS screening questions", "answer ATS questions", "improve my resume", or any reference to `resumejson_cli`.

resumejson_cli Skill

A CLI for converting resumes between PDF / JSON / Markdown and running an AI-powered ATS pipeline (score → questions → answers → review → optimize).

The canonical format is a ResumeJson object validated by a Zod schema. Every command reads or writes that JSON.

Requires: OPENAI_API_KEY environment variable (uses the OpenAI AI SDK, default model gpt-4.1).

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Quick Reference

Goal	Command
Extract resume JSON from PDF	npx resumejson_cli from_pdf -i resume.pdf -o resume.json
Render resume JSON to PDF	npx resumejson_cli to_pdf -i resume.json -o resume.pdf
Render resume JSON to Markdown	npx resumejson_cli to_markdown -i resume.json -o resume.md
Extract resume JSON from Markdown	npx resumejson_cli from_markdown -i resume.md -o resume.json
Score a resume against ATS criteria	npx resumejson_cli ats_score -i resume.json -o ats_score.json
Generate an ATS review	npx resumejson_cli ats_review -i resume.json -o ats_review.json
Generate ATS screening questions	npx resumejson_cli ats_question -i resume.json -o questions.json
Auto-answer ATS questions from resume	npx resumejson_cli ats_answering -i resume.json -q questions.json -o answered.questions.json
Fold answered questions into resume	npx resumejson_cli ats_answered -i resume.json -q answered.questions.json -o answered.resume.json
Optimize resume from an ATS review	npx resumejson_cli ats_optimize -i resume.json -r ats_review.json -o optimized.resume.json

- is accepted as <path> for stdin/stdout.

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Setup

cd packages/resumejson_cli
npm install
npm run build

# Set API key
export OPENAI_API_KEY=sk-...

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Commands

All commands take -i <input> and -o <output>. AI-backed commands also print a human-readable summary to stdout in addition to writing the JSON output file.

Conversion: from_pdf / to_pdf

# PDF -> resume JSON (uses GPT-4.1 vision over rendered PDF pages, cached in SQLite)
npx resumejson_cli from_pdf -i ./resume.pdf -o ./resume.json

# resume JSON -> PDF (renders via Mustache HTML template + Puppeteer)
npx resumejson_cli to_pdf -i ./resume.json -o ./resume.pdf

Conversion: from_markdown / to_markdown

# Markdown -> resume JSON
npx resumejson_cli from_markdown -i ./resume.md -o ./resume.json

# resume JSON -> Markdown
npx resumejson_cli to_markdown -i ./resume.json -o ./resume.md

ats_score

Quick numerical ATS readiness evaluation — use this as a "before / after" gauge.

npx resumejson_cli ats_score -i ./resume.json -o ./ats_score.json

ats_review

Detailed qualitative ATS review (strengths, weaknesses, suggestions). Feeds ats_optimize.

npx resumejson_cli ats_review -i ./resume.json -o ./ats_review.json

ats_question / ats_answering / ats_answered

Three-step loop that surfaces typical ATS screening questions, answers them from the resume, then folds the answers back in to enrich the resume.

# 1. Generate the questions an ATS would ask about this resume
npx resumejson_cli ats_question  -i ./resume.json                              -o ./questions.unanswered.json

# 2. Have the AI answer them using the resume as context
npx resumejson_cli ats_answering -i ./resume.json -q ./questions.unanswered.json -o ./questions.answered.json

# 3. Merge the answers back into a richer resume JSON
npx resumejson_cli ats_answered  -i ./resume.json -q ./questions.answered.json   -o ./resume.answered.json

ats_optimize

Rewrites the resume guided by an ATS review (typically run on the post-ats_answered resume).

npx resumejson_cli ats_optimize -i ./resume.answered.json -r ./ats_review.json -o ./resume.optimized.json

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Workflow: full ATS pipeline

The recommended end-to-end pipeline, mirroring the full_pipeline script in package.json:

# 1. ingest
npx resumejson_cli from_pdf      -i resume.pdf                                  -o resume.json

# 2. baseline score (optional, for before/after comparison)
npx resumejson_cli ats_score     -i resume.json                                 -o resume.ats_score.json

# 3. enrich with answered ATS questions
npx resumejson_cli ats_question  -i resume.json                                 -o questions.unanswered.json
npx resumejson_cli ats_answering -i resume.json -q questions.unanswered.json    -o questions.answered.json
npx resumejson_cli ats_answered  -i resume.json -q questions.answered.json      -o resume.answered.json

# 4. review and optimize
npx resumejson_cli ats_review    -i resume.answered.json                        -o resume.ats_review.json
npx resumejson_cli ats_optimize  -i resume.answered.json -r resume.ats_review.json -o resume.optimized.json

# 5. render the optimized result
npx resumejson_cli to_pdf        -i resume.optimized.json -o resume.optimized.pdf
npx resumejson_cli to_markdown   -i resume.optimized.json -o resume.optimized.md

# 6. (optional) confirm the score improved
npx resumejson_cli ats_score     -i resume.optimized.json -o resume.optimized.ats_score.json

When the user asks to "improve / optimize my resume for ATS", run this full pipeline unless they ask for a single step.

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Output

• All commands write structured JSON (or PDF / Markdown for conversion outputs) to the path given in -o.
• AI-backed commands also print a human-readable pretty-printed summary to stdout.
• Use - for either -i or -o to read from stdin / write to stdout.
• The from_pdf PDF→images step is memoised in .openai_cache.sqlite next to the package, so re-running it on the same PDF is cheap.

Error handling

• Missing OPENAI_API_KEY — every AI command will fail; tell the user to export it before retrying.
• Input JSON that does not match ResumeJsonSchema — the CLI throws a Zod validation error; surface it and ask the user to fix the offending field rather than silently retrying.
• from_pdf on a non-text / image-only PDF still works (it uses the vision model), but very long PDFs are slow and may need a smaller input.