resume-audit
Skill4 starsChanged 3 months agoMITView on GitHub
中文简历反酥化打标技能：扫描简历中的强动词、数字口径、头衔膨胀和证据缺口，输出水分等级、红旗清单与修改优先级；当用户输入“/resume-audit”“简历打假”“查水分”或要求审计简历时使用。
2 other projects use a version of this.
Adopted by
Most recently taken up by
- trac3r00/agent-skillstheir own version, first seen Aug 26, 2026
- shaokeyibb/anti-asu-skillstheir own version, first seen Aug 25, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- shaokeyibb/anti-asu-skills★ 28same name
- trac3r00/agent-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- audit-contribSkill
- deasuSkill
- honest-resumeSkill
- probeSkill
The file
Files
/resume-audit：简历审计
对整份简历做结构化打标，而不是只改一两句文案。默认站在「懂行的面试官」视角。
工作流程
- 读取简历（Markdown / HTML / PDF 文本 / 截图 OCR 结果）与可选的目标 JD。
- 按模块扫描：教育、实习/工作、项目、开源、技能、自我评价/HR 开场白。
- 对每条 bullet 打标签：
证据不足口径模糊团队冒领计划当完成数字无定义头衔过冲工具堆砌同义反复可核验。 - 汇总水分等级：
低/中/高/极高，并给出判定依据（命中红旗数、无证据强主张占比）。 - 输出修改优先级：必须删、必须降级、建议补证据、可保留。
- 用户需要逐条还原叙事时转入
/deasu；开源段落转入/audit-contrib；要生成去包装文件时转入/honest-resume；要模拟面试时转入/probe。
红旗速查
优先参考 references/deasu-dictionary.md。常见红旗包括：
- 「主导 / Owner / 负责人 / 架构师」但无决策与交付边界；
- 「0→1 / 从零搭建」但无时间线、仓库或上线证据；
- 「提升 X% / 降低 Y ms / 覆盖率 100%」无口径、样本或对比基线；
- 「深度参与 / 核心开发」与职责描述只剩调包、改配置、写文档；
- 技能栏堆满框架名，经历中从未出现对应动作；
- 开源贡献只有 contribution graph 截图，无 PR 链接。
默认输出
- 总评（水分等级 + 一句话）；
- 红旗清单（按严重度排序）；
- 分模块审计摘要；
- 修改优先级清单；
- 可选：复制到
assets/claim-audit-report.html风格的本地审计报告（用户指定路径时再写文件）。
边界
- 审计结论必须可追溯到原文句子；禁止空洞的「整体不够真实」。
- 对优秀但表述普通的内容明确标
可核验/可保留，避免为反酥化而反酥化。 - 不把用户真实联系方式写入公开模板。
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.