Analysis updated 2026-05-18
Paste a job description into Claude Code or Cursor and get a tailored one-page PDF resume without writing LaTeX manually.
Get an honest gap report that lists which job requirements your profile lacks rather than AI-generated filler.
Build a master profile from your resume and GitHub repos once, then reuse it automatically for every future job application.
| noahmustafa/open-resume-agent | zabbix/zabbix | bitnami/charts | |
|---|---|---|---|
| Stars | 2 | 5,902 | 10,334 |
| Language | Go Template | Go Template | Go Template |
| Setup difficulty | moderate | hard | hard |
| Complexity | 2/5 | 4/5 | 4/5 |
| Audience | vibe coder | ops devops | ops devops |
Figures from each repo's GitHub metadata at analysis time.
Requires an agentic LLM tool with file and shell access (Claude Code, Cursor, etc.) and a GitHub username for the profile-build step.
Open Resume Agent is a set of three plain Markdown instruction files that turn any AI coding assistant into an automated resume tailor. You drop a job description into chat, and the agent reads the playbooks and produces a one-page, ATS-safe PDF resume tailored for that role, along with a gap report explaining which requirements your profile genuinely does not meet. The project enforces a strict rule against invented experience. If you are underqualified for a role, the system says so in the gap report rather than adding keywords you cannot back up. The final output per application includes a LaTeX source file, a compiled PDF, an ATS readiness score, and a recommendations file that lists any gaps the system could not honestly close. The workflow runs through three slash commands. You run setup once per machine, which downloads two self-contained binaries: an ATS scoring tool and a LaTeX compiler called Tectonic. You run profile-build once per person, which parses your existing resume file, reads your public GitHub repositories, and writes a profile.json that serves as the single source of truth for every resume the system ever produces. Then for each job application, you run tailor, paste in the job description, and the agent handles the rest: selecting which parts of your profile are relevant, writing the LaTeX, compiling the PDF, scoring it against the job description, and revising if the score falls below a threshold. No Docker, Node.js, Python, or servers are needed. The binaries are self-contained and work on Windows, macOS, and Linux. A GitHub username is needed for the profile-build step to fetch your public repositories. The license is MIT.
Markdown playbooks that turn any AI coding assistant into a per-job resume tailor, producing a one-page ATS-safe PDF and an honest gap report without fabricating experience.
Mainly Go Template. The stack also includes Markdown, LaTeX, Go Template.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly vibe coder.
This repo across BitVibe Labs
Verify against the repo before relying on details.