by libnyx · Codex Skill · ★ 110
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/libnyx/LT2MD.git $env:USERPROFILE\.claude\skills\LT2MD
git clone https://github.com/libnyx/LT2MD.git $env:USERPROFILE\.codex\skills\LT2MDTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 110 |
| Forks | 6 |
| Language | Python |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 65/100 |
| Last Updated | 2026-08-23 |
| Created | 2026-08-14 |
| Platforms | codex, python |
| Est. Tokens | ~16k |
English | 简体中文 LT2MD 📄➡️📝 Turn PDFs — long ones, scanned ones, formula- and figure-heavy ones — into reliable Markdown, with every paragraph labeled with the PDF page it came from. It can also repair a Markdown file you converted before. View on GitHub LT2MD is a skill for AI agents. It does two things. It converts a PDF into Markdown you can reuse and trace back to the source page.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: