resume-as-code keeps your resume as version-controlled structured data: a folder of small files (one per job, school, project, skill), tracked in git, that you never hand-edit. Instead you talk to an AI agent, and the agent runs the resume command-line tool for you.
“Add my new role: Staff Engineer at Acme, started March 2025.” “Import my old resume” — point it at a PDF or your LinkedIn export. “Tailor my resume for this job and export a PDF.”
The data stays clean and consistent because a precise, deterministic CLI does the writing — and every change is a git commit you can review or roll back.

Get started

Install the binary and let your agent lead a guided first-time setup.

Command reference

Every resume command, grouped by what you’re doing.

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Why resume-as-code

Structured, not a blob

JSON Resume schema plus a LinkedIn extension, one YAML file per entry. Queryable, diffable, durable.

Git is first-class

Every edit auto-commits. Full history, instant rollback, and branch-based resume variants.

Agent-driven

A deterministic CLI does the writing; your AI agent supplies the judgment. No hand-editing YAML.

Tailor for every job

Branch a tailored variant per posting, track applications, and score how well you match.

Import what you have

A PDF, a Word doc, a LinkedIn export, or a JSON Resume file — your agent imports and structures it.

Export anywhere

Render to PDF, HTML, or DOCX with themes — or emit the canonical JSON Resume document.

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How it works

You don’t learn commands. You install the binary once, point your agent at it, and then just talk:
  1. Install the resume binary and the agent skill (one command each).
  2. Open your agent in a folder — it detects a first run and leads you through setup, including offering to import an existing resume.
  3. Converse. Add roles, tailor for a job, export a PDF — the agent runs the CLI; git records everything.

Start here

The Getting Started guide walks through install, agent setup, and the guided first run.