by XBuilderLAB · Claude Skill · ★ 172
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
帮你在 AI 时代找到一份高薪 × 你学得动 × 不会被 AI 吃掉的工作，并给出个性化学习陪跑计划。能力匹配 + 可学性闸门 + BOSS 直聘真实招聘数据 + 反诈。
| Stars | 172 |
| Forks | 13 |
| Language | JavaScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 60.8596800308234/100 |
| Last Updated | 2026-06-27 |
| Created | 2026-06-27 |
| Platforms | claude-code, node |
| Est. Tokens | ~3k |
Looking for a cheat-on-skill alternative? If you're comparing cheat-on-skill with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops t
Claude Code Skills for software engineering workflows - Git automation, testing, and code review
Open-source sandboxes where coding agents build and deploy. Spin up isolated environments where Claude Code, C
HeyClaude (formerly Claude Pro Directory) is a searchable collection of pre-built AI skills, agents, MCP serve
Security operations toolkit for AI coding agents. Give Claude Code 25+ skills to catch vulnerabilities, scan c
🏛 [UNDER CONSTRUCTION] A (roman) claude plugin marketplace
Explore other popular claude skill tools:
cheat-on-skill is 帮你在 AI 时代找到一份高薪 × 你学得动 × 不会被 AI 吃掉的工作，并给出个性化学习陪跑计划。能力匹配 + 可学性闸门 + BOSS 直聘真实招聘数据 + 反诈。. It is categorized as a Claude Skill with 172 GitHub stars.
cheat-on-skill is primarily written in JavaScript. It covers topics such as ai-career, anthropic, career-transition.
You can find installation instructions and usage details in the cheat-on-skill GitHub repository at github.com/XBuilderLAB/cheat-on-skill. The project has 172 stars and 13 forks, indicating an active community.
cheat-on-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to cheat-on-skill on Agent Skills Hub include code-on-incus, claude-skills-marketplace, runtm. 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: