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 CheshireMew · Codex Skill · ★ 95
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is 100x-learning safe to install? View the security audit →
中文 · English · 日本語 反馈 <img src="https://img.shields.io/github/forks/CheshireMew/100x-learning?style=fl
| Stars | 95 |
| Forks | 5 |
| Language | Python |
| Category | Codex Skill |
| License | MPL-2.0 |
| Quality Score | 62.7797743986711/100 |
| Last Updated | 2026-09-02 |
| Created | 2026-07-13 |
| Platforms | codex, python |
| Est. Tokens | ~15k |
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100x-learning is A Codex skill for research-led and practice-led learning. It is categorized as a Codex Skill with 95 GitHub stars.
100x-learning is primarily written in Python. It covers topics such as agent-skill, content-strategy, knowledge-management.
You can find installation instructions and usage details in the 100x-learning GitHub repository at github.com/CheshireMew/100x-learning. The project has 95 stars and 5 forks, indicating an active community.
100x-learning is released under the MPL-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to 100x-learning on Agent Skills Hub include anti-slop-writing, membrane, membrane. 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: