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 career-ops-hq · Codex Skill · ★ 71.6k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is career-ops safe to install? View the security audit →
English Türkçe I spent months applying to jobs the hard way. So I engineered the system I wish I had. Companies use AI to filter candidates. I just gave candidates AI to choose companies. Now it's open source. <p align="c
| Stars | 71,570 |
| Forks | 13,501 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 60.3114213925223/100 |
| Open Issues | 536 |
| Last Updated | 2026-09-14 |
| Created | 2026-04-04 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~21k |
These tools work well together with career-ops for enhanced workflows:
Looking for a career-ops alternative? If you're comparing career-ops with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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career-ops is Open-source AI job search: scan job portals, evaluate listings into a structured A-H report with a global 1-5 score, tailor your CV, track applications — runs locally in your AI coding CLI (Claude Cod. It is categorized as a Codex Skill with 71.6k GitHub stars.
career-ops is primarily written in JavaScript. It covers topics such as ai, ai-agent, anthropic.
You can find installation instructions and usage details in the career-ops GitHub repository at github.com/career-ops-hq/career-ops. The project has 71.6k stars and 13501 forks, indicating an active community.
career-ops is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to career-ops on Agent Skills Hub include career-ops, ai-job-search, Agent-Reach. 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: