No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by weeelin98 · Codex Skill · ★ 101
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ResumeDom safe to install? View the security audit →
ResumeDom Build one truthful career record. Tailor every application without inventing evidence. English · 简体中文 ResumeDom is a Codex skill for reviewing, rewriting, tailoring, and generating evidence-backed US technology resumes. One source of truth for career facts; one focused resume for each application. Quick start · Capabilities · Resume modes · LaTeX · Rules Star History <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=weeelin98/resumedom&type=date&legend=top-le
| Stars | 101 |
| Forks | 1 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 49.6924427841566/100 |
| Last Updated | 2026-09-26 |
| Created | 2026-01-21 |
| Platforms | codex, python |
| Est. Tokens | ~5k |
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ResumeDom is Evidence-first Codex skill for reviewing, rewriting, tailoring, and generating ATS-readable US tech resumes for CS interns and new grads.. It is categorized as a Codex Skill with 101 GitHub stars.
ResumeDom is primarily written in Python.
You can find installation instructions and usage details in the ResumeDom GitHub repository at github.com/weeelin98/ResumeDom. The project has 101 stars and 1 forks, indicating an active community.
The top alternatives to ResumeDom on Agent Skills Hub include theorist. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: