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 jiankang1991 · Codex Skill · ★ 88
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is nsfc-benzi-audit safe to install? View the security audit →
NSFC 本子把脉 给国自然申请书做一次结构化体检:找逻辑断点,给修改抓手。 是一个用于国家自然科学基金(NSFC/国自然)申请书初稿诊断的 Agent Skill。它面向已经有草稿的申请人,帮助从题目、摘要、立项依据、关键科学问题、研究内容、创新点、研究基础、图表、文献和形式栏目等角度生成修改建议。 它不是代写工具,不承诺申请成功,也不替代申请人自己的科学判断、同行专家建议、依托单位要求和基金委官方指南。 交流群 有问题、有案例、有改进建议,欢迎进群交流使用心得。 QQ 群:nsfc-skill交流,群号 1062928117 快速开始 把申请书 PDF、DOCX、Markdown、纯文本,或核心片段贴给 Agent。若提供已中本子作为对照样本,先做匿名化处理,并说明项目类型、获资助年份、粗略学科/申请代码和研究属性。 适用场景 青年、面上、地区等项目申请书已有初稿,需要做结构性体检。 想检查题目、摘要、关键科学问题和创新点是否互相支撑。 想检查科学问题
| Stars | 88 |
| Forks | 10 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 60.6556720748131/100 |
| Last Updated | 2026-09-14 |
| Created | 2026-06-30 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~15k |
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nsfc-benzi-audit is 一个用于国家自然科学基金(NSFC/国自然)申请书初稿诊断的 Agent Skill. It is categorized as a Codex Skill with 88 GitHub stars.
nsfc-benzi-audit is primarily written in Python. It covers topics such as agent-skills, claude-code, codex.
You can find installation instructions and usage details in the nsfc-benzi-audit GitHub repository at github.com/jiankang1991/nsfc-benzi-audit. The project has 88 stars and 10 forks, indicating an active community.
nsfc-benzi-audit is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to nsfc-benzi-audit on Agent Skills Hub include ai-skills, tutor-skills, ask-user-questions-mcp. 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: