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 SenmuuuuW · Codex Skill · ★ 207
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is universal-diagnostic-tutor-skill safe to install? View the security audit →
🧠 Universal Diagnostic Tutor Skill A diagnosis-first AI tutor that decides what the learner needs next — without making them choose modes or features. English | 中文 User Guide · Command Surface · Examples · Changelog Universal Diagnostic Tutor Skill is a Markdown-only AI tutor behavior layer for STEM, mathematics, programming, AI/CS, and exam review. It diagnoses the learner's gap, chooses the next best teaching step, and checks evidence before advancing. The difference: it is not answer-first. It identifies the subject, concept, prerequisite, notation, method, or reasoning gap before choosing a compact teaching move. It is not a course platform, database, RAG system, or hidden-memory service. 🚀 Quick Start Copy the [Lite P
| Stars | 207 |
| Forks | 6 |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62.7664107663484/100 |
| Last Updated | 2026-09-15 |
| Created | 2026-06-26 |
| Platforms | codex |
| Est. Tokens | ~18k |
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universal-diagnostic-tutor-skill is One diagnosis-first AI tutor for STEM, AI/CS, and beyond — no mode or command menu. It decides the next useful teaching step, checks understanding, and builds mastery.. It is categorized as a Codex Skill with 207 GitHub stars.
You can find installation instructions and usage details in the universal-diagnostic-tutor-skill GitHub repository at github.com/SenmuuuuW/universal-diagnostic-tutor-skill. The project has 207 stars and 6 forks, indicating an active community.
universal-diagnostic-tutor-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to universal-diagnostic-tutor-skill on Agent Skills Hub include human-skill-tree, codex-multi-auth, universal-examprep-skill. 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: