by orange2ai · Agent Tool · ★ 113
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git clone https://github.com/orange2ai/podcast-to-article.gitTaken from the project's README on GitHub. Check the security audit before running it.
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. Full audit →
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 | 113 |
| Forks | 6 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 60/100 |
| Last Updated | 2026-10-08 |
| Created | 2026-10-07 |
| Platforms | python |
| Est. Tokens | ~14k |
播客转文章 · podcast-to-article 把一期播客的逐字稿，整理成能直接发的长文。多人对谈、单人访谈都行，中文和英文素材都行。 逐字稿的轴是发言人和时间，文章的轴是话题和判断。这个 skill 做的就是换轴。 为什么需要它 直接让模型「把逐字稿写成文章」，出来的一般是三种东西。 一种是记流水账，满篇「张三说……李四说……王五说……」，读起来像会议纪要。另一种是抽象化，数字和细节全丢了，换成一堆「行业正在加速」「生态逐渐成熟」，很顺，但没有一句是新信息。第三种最不容易发现：改写过度。发言人的原话被压成第三人称概述，「他说」被换成陈述句，稿子读起来像记者的二手转述，读不出那个人说话的样子。 所以规矩是三条：拆掉发言人的脚手架，保留事实的颗粒度，留住原话的语气。 前两条管信息，第三条管人。...
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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: