Maintainer of this skill?
Automated security scan — not a certification.
by yanliudesign
Full job-hunt Claude skill bundle — Job Description decoder + Resume builder (11 templates) + Behavioral Interview / story bank. Three self-contained sub-skills with a top-level router.
# Add to your Claude Code skills
git clone https://github.com/yanliudesign/offer-toolkit-skillGuides for using ai agents skills like offer-toolkit-skill.
Last scanned: 7/25/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-07-25T06:18:05.016Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}See how offer-toolkit-skill compares with popular alternatives.
offer-toolkit-skill is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by yanliudesign. Full job-hunt Claude skill bundle — Job Description decoder + Resume builder (11 templates) + Behavioral Interview / story bank. Three self-contained sub-skills with a top-level router. It has 539 GitHub stars.
Yes. offer-toolkit-skill passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/yanliudesign/offer-toolkit-skill" and add it to your Claude Code skills directory (see the Installation section above). offer-toolkit-skill ships a SKILL.md manifest, so compatible agents can discover and load it automatically.
offer-toolkit-skill is primarily written in HTML. It is open-source under yanliudesign on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh offer-toolkit-skill against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
一整套求职 skill 的聚合入口。六条子 skill 各自独立可用，也可以组成从找岗位到签 offer 的完整链路：
种子 JD + 简历 → [job-hunt-skill] 搜索 · 去重 · 证据分层 · HTML 清单
↓ 选中岗位
[Job Description Skill] 解码 JD · 出 Offer Strategy Report
↓ 决定投
[Resume Skill] tailor + 美化 · 12 套模板 · 单文件 HTML
↓ 拿到面试
[BQ Skill] 挖故事 · 建故事库 · STAR 化 · 模拟面试
↓ 拿到 offer
┌ 一份 offer ───────────────→ [Salary Negotiation] 谈 package
└ 多份 offer → [Offer Compare] 选 offer ────────┘
顶层原则（六条子 skill 共用）：
| 用户说的话 | 走哪个子 skill |
|---|---|
| "帮我找工作" / "在 LinkedIn 搜适合我的岗位" / "根据这份 JD 找相似职位" / "根据简历推荐岗位" / "整理职位清单" | → job-hunt-skill/ |
| 贴出一份 JD / "这个岗位我该不该投" / "帮我看看这份工作" / "match score" / "面试会问什么" | → job-description-skill/ |
| "帮我美化简历" / "改简历" / 上传 PDF/docx / "我没有简历帮我做一份" / "换个模板" / LinkedIn 导入 | → resume-skill/ |
| "帮我准备 behavioral 面试" / "Tell me about a time…" / "帮我挖一个面试故事" / "STAR 怎么写" / "建我的故事库" / "Amazon LP 怎么准备" | → bq-skill/ |
| "两份 offer 怎么选" / "A 还是 B" / "compare offers" / "算 4 年 TC" | → offer-compare-skill/ |
| "帮我谈薪" / "怎么 counter" / "能不能多要 RSU" / "salary negotiation" | → salary-negotiation-skill/ |
| 一次交出 JD + 简历，想要"全套准备好" | → job-description-skill/ → resume-skill/ → bq-skill/ → 有多份 offer 先 offer-compare-skill/ → salary-negotiation-skill/ |
判断不了就问一句：
"你现在在求职链路的哪一步？ · 还在找机会，希望自动发现并整理匹配岗位 → job-hunt-skill · 看到一个心动岗位，还没决定要不要投 → JD Skill · 已经决定投，需要一份简历 → Resume Skill · 已经拿到面试，要准备行为面试题 → BQ Skill · 已经拿到多份 offer，不知道选哪份 → Offer Compare Skill · 已经选定 offer，想把 package 谈高 → Salary Negotiation Skill"
每个子目录都是一份完整的 skill（各自有 SKILL.md + 独立 README）。可以聚合装，也可以只装其中一个。
根据简历、目标方向或种子 JD 生成搜索画像，执行多组公开职位查询，采集、去重并区分已核验事实与方向性推断。默认保留所有通过硬条件的唯一岗位，输出可搜索筛选的单文件 HTML 清单；只搜索分析，不自动投递、不处理登录凭据、不绕过访问限制。
把任何 JD 翻译成一份 10 节的 Offer Strategy Report（HTML 单文件，自动打开浏览器）：TL;DR 结论 · Match Score · Interview Probability · 公司背景 · JD 深度解码 · JD ↔ 简历逐条比对 · Gap 与补救 · 为什么投/不投 · 薪资 · 下一步 · Top 10 面试题 · 6 周行动计划。
三步：贴 JD → 给简历 → 自动生成 HTML 报告并打开。
把"我需要一份好看的简历"变成稳定流程：所有素材先汇入 schema/resume-data.md 定义的标准数据结构，再套模板渲染。换模板只是换皮，内容不丢。
三条入口：美化已有简历 / LinkedIn 导入 / 对话式建简历。 12 套打印级模板：Classic-ATS · Ledger · Modern Sidebar · Pillar · Elegant Serif · Atelier · Timeline · Swiss · Executive · Editorial Banner · Photo Corporate · Photo Minimal。 每次渲染同时输出锁定版（直接 Cmd+P 存 PDF）和可编辑版（浏览器里点字微调 + 浮动工具条）。
不是背答案，而是建一套可复用的职业故事库。流程：挖掘 → 结构化 → 打标 → 存库 → 复用。
能做的事：
结构化对比两份或多份 offer 的 4 年 TC、成长、AI 敞口、公司与团队风险、晋升、生活方式和未来跳槽价值。输出一份 HTML Offer Decision Report，并给出明确推荐，而不是把选择留给用户。
三步：贴多份 offer → 补充 priorities 与当前处境 → 生成报告并打开。
诊断 Base、RSU、Sign-on 和 Bonus 的谈判空间，识别用户与招聘官双方杠杆，生成谈判顺序、可直接使用的中英文电话/邮件脚本、两轮 counter 模拟和明确 stop-line。
三步：贴 offer → 补充竞争 offer、deadline 与风险偏好 → 生成 HTML Negotiation Playbook 并打开。
把整个 offer-toolkit-skill/ 目录放进你的 skill 目录（例如 ~/.claude/skills/ 或 VS Code 的 prompts 目录），六条子 skill 会一起被发现。
只想装其中一个？ 直接把对应子目录（如 resume-skill/）单独复制过去也可以，每个子 skill 都是自包含的。
MIT — fork, remix, ship your own version.
Created by Dreameryanyan · LinkedIn · X · 小红书
中文 · English
Six job-hunt tools in one agent skill pack — Search · JD · Resume · BQ · Compare · Negotiate.
Six job-hunting tools bundled as an agent skill pack. Use the whole thing, or just the piece you need — each sub-folder works on its own.
| Stage | Skill | What it does |
|---|---|---|
| 0 · Discover opportunities | job-hunt-skill | Build a deduplicated, searchable HTML job list. |
| 1 · See a job you want | job-description-skill | Decode the JD and get an Offer Strategy report. |
| 2 · Decide to apply | resume-skill | Tailor and polish your resume with 12 print-ready templates. |
| 3 · Land the interview | bq-skill | Mine stories, build a story bank, and prep BQs. |
| 4 · Compare offers | offer-compare-skill | Compare TC, growth, and risk, then get a clear recommendation. |
| 5 · Negotiate the package | salary-negotiation-skill | Diagnose leverage, generate scripts, and set stop-lines. |
Drop the whole offer-toolkit-skill/ folder into your skills directory (e.g. ~/.claude/skills/ or VS Code's prompts folder). All six sub-skills get picked up.
Only want one? Copy just that sub-folder — each one is self-contained.
🔒 Your generated files stay local. Reports, resumes, and story banks are written to your machine. Your prompts and attachments are processed according to the data policy of the agent and model provider you use.
Once installed, copy any prompt into your Claude Code / VS Code chat:
Should I apply to this? I'll paste the JD link or full text next.
Use this JD and my resume to find matching LinkedIn jobs.
Beautify my resume. I'll attach the PDF next.
Prep me for behavioral interviews.
Compare these two offers and tell me which one to take.
Help me negotiate this offer.
The router picks the right sub-skill. You get an HTML report / resume / story bank on your desktop, ready to open.
No. Install the whole toolkit for automatic routing across the job-search journey, or copy a single sub-folder if you only need one skill. Every sub-skill is self-contained.
No. The full sequence is useful when you are starting a job search, but you can enter at any stage. Already have an interview? Start with BQ Skill. Already have offers? Go straight to Offer Compare or Salary Negotiation.
Make sure the folder still contains its SKILL.md, then start a new chat or reload your agent after installation. You can also invoke it explicitly, for example: “Use resume-skill to improve this resume.”
Yes, when the client supports SKILL.md-style agent skills or workspace instructions. Installation directories and skill-discovery behavior vary by client, so follow that client's current documentation.
The toolkit itself is open source and does not require a separate API key. You still need access to a compatible AI client, whose subscription, usage fees, and authentication requirements depend on the pr