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 M1n-n9 · Codex Skill · ★ 621
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is paper-lifecycle safe to install? View the security audit →
Paper Lifecycle Skills 中文 · English 中文 Switch to English 现在是一个科研写作 skills suite。根目录只做项目说明，真正可安装、可调用的 skill 是两个平级目录： 两个 Skill Review Revision 路径： 用途：对已有论文、初稿、被拒稿件或已有明确方向的 idea 做审稿式体检和修改规划。它会检查问题是否真实，insight 是否成立，novelty 是否站得住，method 是否服务于机制，experiments 是否支撑 claim，writing 是否把审稿人带到正确理解。 适合： 论文 PDF、LaTeX、Word 或 Markdown 初稿诊断 A 会、期刊或 workshop 投稿前 checklist introduction、related work、method、experiments 等逐节修改 theory、statistics、reproducibility、figures/tables 审计 调用示例： Rebuttal Response 路径： 用途：专门处理审稿意见和 rebuttal。它不是泛泛润色回复，而是把 reviews 拆成 AC 能判断的证据包：哪些 concern 会影响接收，哪些 reviewer 可能被说服，优先补哪些证据，怎样写 AC-facing summary，怎样逐 reviewer 回复，怎样纠正事实错误但不显得攻击 reviewer。 适合： 收到 reviews 后做问题分类和优先级排序 写 AC-facing executive summary 回复 novelty、baseline、实验设置、方法动机、scope、事实误解 检查 rebuttal 语气，删掉过度道歉、硬刚、空泛承诺 生成 rebuttal checklist 和 camera-ready promise list 调用示例： C
| Stars | 621 |
| Forks | 38 |
| Category | Codex Skill |
| Quality Score | 41.6612864380424/100 |
| Last Updated | 2026-06-16 |
| Created | 2026-06-15 |
| Platforms | codex |
| Est. Tokens | ~15k |
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paper-lifecycle is Codex skill for full academic paper lifecycle analysis and revision. It is categorized as a Codex Skill with 621 GitHub stars.
You can find installation instructions and usage details in the paper-lifecycle GitHub repository at github.com/M1n-n9/paper-lifecycle. The project has 621 stars and 38 forks, indicating an active community.
The top alternatives to paper-lifecycle on Agent Skills Hub include Claude-to-IM-skill, pi-skills, agent-skill-creator. 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: