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 GresonKwan · Agent Tool · ★ 403
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is JobOK safe to install? View the security audit →
Job OK 面向中文求职者的证据驱动求职 Agent Skill:不编经历,不自动海投,只把真实经历变成可投递、可面试、可复盘的求职证据系统。 Why Job OK 很多求职者的问题不是“完全没有能力”,而是: 简历只会写“参与、协助、负责”,没有动作和结果; 面试一追问项目细节就散; JD 看了很多,但不知道自己该投什么; 用 AI 改简历时,很容易从“表达优化”滑向“包装和编造”。 Job OK 的思路是把求职拆成一个本地工作流: 它不是求职捷径,而是一套逼你把自己讲清楚的系统。 Features What It Will Not Do Job OK 不是“自动投递神器”: 不编造经历; 不承诺 offer; 不自动投递; 不自动私信 HR; 不批量爬取招聘平台; 不绕过登录、验证码或平台限制; 不替企业做候选人排名或招聘决策。 Quick Start 让 Agent 帮你安装 在 Codex、Claude Code 或其他支持 Skill 的 Agent 里直接说: Agent 会把仓库安装到对应的本地 Skill 目录。安装完成后,重启你的 Agent
| Stars | 403 |
| Forks | 4 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64.7771994646225/100 |
| Last Updated | 2026-06-18 |
| Created | 2026-06-17 |
| Platforms | python |
| Est. Tokens | ~3k |
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JobOK is Job OK: 面向中文求职者的证据驱动求职 Agent Skill,支持优势挖掘、岗位匹配、简历优化、面试训练和投递跟踪。. It is categorized as a Agent Tool with 403 GitHub stars.
JobOK is primarily written in Python.
You can find installation instructions and usage details in the JobOK GitHub repository at github.com/GresonKwan/JobOK. The project has 403 stars and 4 forks, indicating an active community.
JobOK is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to JobOK on Agent Skills Hub include awesome-android-agent-skills, agent-skills, claude-code-skill-factory. 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: