resume-skill

resume-skill is a skill for Claude Code, Codex from yanliudesign/offer-toolkit-skill. It costs 160 tokens per session (2,453 once invoked), scanned A, original, MIT.

A resume builder and editor that turns an existing resume or information from LinkedIn into structured content and formats it as a printable HTML resume. It can also create a resume through a question-and-answer conversation.

In plain words
What is it for?
Use it to import, diagnose, rewrite, and format resumes, choose among four templates, or save the result as a PDF from your browser.
Why use it?
It gives you one process for improving an old resume or creating one from scratch, while keeping the content based on facts you provide. ATS means software employers use to scan resumes for matching information.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /Users/yanliu/Desktop/Claude.

Good fit Use it to import, diagnose, rewrite, and format resumes, choose among four templates, or save the result as a PDF from your browser.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for resume-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/yanliudesign/offer-toolkit-skill/resume-skill/github.svg)](https://agentmods.dev/skills/yanliudesign/offer-toolkit-skill/resume-skill)
Your own site
<a href="https://agentmods.dev/skills/yanliudesign/offer-toolkit-skill/resume-skill"><img src="https://agentmods.dev/badge/skills/yanliudesign/offer-toolkit-skill/resume-skill/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for resume-skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/yanliudesign/offer-toolkit-skill/resume-skill"><img src="https://agentmods.dev/badge/skills/yanliudesign/offer-toolkit-skill/resume-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 160 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,453 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00160 $0.02453
Opus 5 $0.00080 $0.01226
Sonnet 5 $0.00032 $0.00491
Haiku 4.5 $0.00016 $0.00245

Measured 11d ago against content hash e2057520ca4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

resume-skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

resume-skill/SKILL.md · 104 lines

How it starts

The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Resume Skill — 简历生成与美化

把"我需要一份好看的简历"变成一条稳定流程:所有素材先汇入一份标准化的结构化数据,再套模板渲染。这样换模板只是换皮,内容不丢;美化和从零创建走的是同一条后半段。

三条第一原则

  1. 绝不杜撰。 所有经历、职责、数字都必须来自用户真实提供的内容。可以引导、追问、帮他把模糊的说清楚、把弱 bullet 改强,但绝不编造公司、职位、成果或量化数字。任何数字都要向用户求证,不确定就标记 [待确认] 而不是猜一个。
  2. 一次只问一个问题。 对话式建简历是访谈不是问卷。问一个 → 等回答 → 顺着追问。永远不要一次抛一串问题。
  3. 先结构化,再渲染。 不管入口是哪条,都先把内容整理成 schema/resume-data.md 定义的字段,确认无误后才套模板出 HTML。

路由:用户进来时先判断意图

用户说的话 走哪条流程
"帮我美化简历" / "改简历" / 上传了一份已有简历(PDF/docx/txt/md) 美化已有简历prompts/beautify.md
"我还没简历,这是我 LinkedIn" / 贴出 linkedin.com 链接 LinkedIn 导入prompts/linkedin-import.md
"我没有简历,帮我做一份" / "通过聊天帮我做" 对话式建简历prompts/interview.md
"换个模板" / "这套不好看" 已有结构化数据时,直接重渲染(见下方渲染流程)

判断不了就问一句:

"你是已经有一份简历想美化,还是从零开始做一份?从零的话,你更想贴 LinkedIn 链接让我导,还是咱们聊一聊我帮你问出来?"


美化已有简历

详见 prompts/beautify.md。要点:

  1. 读取用户提供的简历(可读 PDF / 复制粘贴的文本 / Word 导出)。Claude 可直接 Read PDF。
  2. 解析schema/resume-data.md 的字段,缺失项标 [缺失]
  3. 诊断(对照 guides/writing-tips.md):哪些 bullet 没有量化结果、哪些是职责堆砌而非成果、排版/长度/时间线问题、ATS 风险。给出一份简短诊断清单。
  4. 征求同意再改内容:问用户"我可以顺手把这几条弱 bullet 改强吗?(不改事实,只改表达)"。用户同意才改,且改完逐条让其确认数字。
  5. 选模板 → 渲染(见下方)。

LinkedIn 导入

详见 prompts/linkedin-import.md。要点:现实是 LinkedIn 有登录墙,直接抓公开 URL 经常被拦。流程会先尝试 WebFetch,拿不到就引导用户用 LinkedIn 的"Save to PDF"导出个人资料或复制粘贴各板块内容,再解析进 schema。


对话式建简历

详见 prompts/interview.md。一问一答,按 联系方式 → 目标岗位 → 每段经历(公司/职位/时间 → 做了什么 → 成果数字) → 教育 → 技能 的顺序,挖一段结构化一段,最后汇总进 schema。


渲染流程(三条入口共用的后半段)

  1. 确认结构化数据:把整理好的 resume-data 内容回显给用户,确认无误(尤其数字)。
  2. 选模板:13 套,问用户偏好(默认推荐 Classic/ATS,因为海投最稳):
    模板 文件 适合 ATS
    Classic / ATS templates/classic-ats.html 单栏无花哨,机器可解析,大公司海投最稳 ✅ 友好
    Ledger 学术工程 templates/ledger.html LaTeX 风衬线,公司/日期两端对齐,嵌套子弹,软件/数据/工程岗 ✅ 友好
    Tech 紧凑 templates/tech-compact.html 高信息密度+等宽点缀,工程师把多项目塞进一页 🟡 尚可
    Modern 侧栏 templates/modern-sidebar.html 双栏+深色侧边栏,现代感强 🟡 一般
    Pillar 信息卡 templates/pillar.html Enhancv 风,蓝点缀+技能胶囊+图标成就+语言进度点,产品/市场/PM 🟡 一般
    Elegant 衬线 templates/elegant-serif.html 衬线居中编辑风,设计/咨询/市场等偏人文岗 🟡 一般
    Atelier 极简 templates/atelier.html 大量留白+细字大写名+竖线分栏,设计/创意/审美岗 🟡 一般
    Timeline 时间轴 templates/timeline.html 左侧竖向时间轴脊柱,一眼看出职业成长轨迹 🟡 一般
    Swiss 栅格 templates/swiss.html 瑞士栅格,粗体 Helvetica + 红点缀,设计/品牌/创意 🟡 一般
    Executive 高管 templates/executive.html 藏青衬线,稳重有分量,金融/咨询/高管/资深领导 🟡 一般
    Editorial 刊物 templates/editorial-banner.html 三栏刊物式顶部 + 红衬线 + 底部已名巨型色带,品牌/内容/编辑 🟡 一般
    Photo Corporate 公司头像 templates/photo-corporate.html 深色 banner + 圆形头像,侧栏带技能进度条 + 竖向时间轴 + References,营销/项目/商务 🟡 一般
    Photo Minimal 红点约头像 templates/photo-minimal.html 红点缀 + 分体衬线名字 + 圆形头像,侧栏 Awards + Skills,设计/创作/portfolio 🟡 一般

Read the full file on GitHub · 104 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 104 lines · 160 tokens per session scan A e2057520ca4a

Subscribe to this mod's changes

resume-skill is a skill published in the GitHub repository yanliudesign/offer-toolkit-skill (425 stars, last pushed today), licensed MIT. It adds 160 tokens to every session and 2,453 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.