career-ops-china: Skill for Claude Code

.claude/skills/career-ops/SKILL.md

career-ops is a skill for Claude Code from shuheng-mo/career-ops-china. It costs 30 tokens per session (1,509 once invoked), scanned A, original, MIT.

A Chinese-language job-search command center for mainland China. It evaluates roles, creates tailored resumes, scans job portals, and tracks applications.

In plain words
What is it for?
Use it to assess one or more job offers, research companies, create PDF resumes, compare courses or portfolio projects, contact people, fill forms, process saved job listings, and track applications.
Why use it?
It brings separate job-search tasks into one workflow and accounts for Chinese recruiting sites that may block automatic page reading.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: mentions subagents.

This is shuheng-mo/career-ops-china's own configuration. It tells Claude Code how to work on career-ops-china itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything career-ops-china configures →

Reuse

Borrowing it

Nothing to install: this file belongs to shuheng-mo/career-ops-china. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/shuheng-mo/career-ops-china/main/.claude/skills/career-ops/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/shuheng-mo/career-ops-china

Made for: Claude Code.

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 career-ops

README.md
[![agentmods](https://agentmods.dev/badge/skills/shuheng-mo/career-ops-china/career-ops/github.svg)](https://agentmods.dev/skills/shuheng-mo/career-ops-china/career-ops)
Your own site
<a href="https://agentmods.dev/skills/shuheng-mo/career-ops-china/career-ops"><img src="https://agentmods.dev/badge/skills/shuheng-mo/career-ops-china/career-ops/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 career-ops

Your own site · 80×15
<a href="https://agentmods.dev/skills/shuheng-mo/career-ops-china/career-ops"><img src="https://agentmods.dev/badge/skills/shuheng-mo/career-ops-china/career-ops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,509 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00030 $0.01509
Opus 5.5 $0.00012 $0.00604
Sonnet 5.5 $0.00006 $0.00302
Haiku 4.5 $0.00003 $0.00151

Measured 9d ago against content hash bf6560c3b972, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

career-ops 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 9d 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.

.claude/skills/career-ops/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

career-ops — Router(中国大陆版)

Mode Routing

根据 {{mode}} 决定模式:

输入 Mode
(空 / 无参数) discovery — 显示命令菜单
JD 截图(图片附件) auto-pipeline(推荐主路径,国内 Boss/Mokahr 等反爬平台必用)
JD 文本(粘贴) auto-pipeline
岗位 URL(无子命令) auto-pipeline — 但国内 URL 90% 抓不到 JD,会让用户截图
offer offer(单岗位评估 A-F)
offers offers(多 offer 对比)
contact contact(脉脉/微信/LinkedIn 触达)
deep deep(公司调研 prompt)
pdf pdf(生成定制 PDF)
training training(评估课程/证书)
project project(评估 portfolio 项目)
tracker tracker(查看申请状态)
pipeline pipeline(处理待办 URL inbox)
apply apply(实时表单填写助手)
scan scan(线索发现,仅 URL+标题,不取 JD)
radar radar(管理远程"求职线索雷达"定期 routine — 创建/查看/立即跑/改节奏)
inbox inbox(处理 bookmarklet 捕获的 JD 文件,自动评估)
story-sync story-sync(扫 reports/* 抽取 Block F,累积到 story-bank.md)
evolve / evolve init / evolve dig / evolve status evolve(简历进化:深挖问卷 → 事实账本 → cv.md 版本 + 传导)
batch batch(批量处理)

Auto-pipeline 检测: 如果 {{mode}} 不是已知子命令但包含:

  • JD 文本(出现关键词:"岗位职责"、"任职要求"、"工作描述"、"responsibilities"、"requirements"、公司名 + 岗位名)
  • 图片附件(截图)
  • 岗位 URL

→ 执行 auto-pipeline。

如果 {{mode}} 既不是子命令也不像 JD,显示 discovery。

🇨🇳 中国大陆使用规则:

如果用户给的是国内招聘门户 URL(zhipin.com / liepin.com / lagou.com / mokahr.com / feishu.cn 等),先尝试 WebFetch 一次,失败就立刻停止自动化尝试,让用户截图给你。不要在反爬上反复挣扎。

LinkedIn 例外: linkedin.com/jobs/view/… 链接不用截图,直接跑 npm run linkedin -- <链接>(走 LinkedIn 免登录接口,JD 存进 inbox/),再按 inbox 流程评估。搜索页链接(/jobs/search?…,常带 trk=missing_jd_redirect)说明原岗位已下线,没有 ID 可取。


Discovery Mode(无参数时)

输出下面这段紧凑 cheatsheet(不要展开成长版菜单;输入框上方已有 argument-hint,正文不需重复列子命令的全部说明):

career-ops — 中国大陆求职指挥中心

🎯 主路径:JD 截图 / 粘贴文本 / 公司+岗位 URL → 直接发给我 → 自动评估 + report + PDF + tracker

⚡ 子命令(/career-ops <name>):
  线索 & 批处理   scan       radar      inbox       pipeline    batch
  单岗位          offer      offers     pdf         contact     deep        apply
  追踪 & 沉淀     tracker    story-sync  evolve
  ROI 评估        training   project

🛰️ radar:每 2 天云端自动扫上海/杭州 AI应用·Agent 新岗,出线索清单(/career-ops radar 管理)

⚠️ 国内 URL(Boss/拉勾/猎聘/Mokahr/飞书)90% 抓不到 JD → 截图最快
🐧 腾讯招聘搜索页整页拉:npm run tencent -- "<search.html 链接>" --days 30 --fetch
🦘 美团招聘按关键词拉:npm run meituan -- agent --city 上海,深圳 --days 21 --fetch
🔗 LinkedIn 链接 / 搜岗:npm run linkedin -- <链接>  ·  npm run linkedin -- search "关键词" --city 上海 --days 7
🔖 bookmarklet:tools/README.md(一次安装,之后任意 JD 页一键 → inbox)

不确定哪个?直接发 JD 给我(auto-pipeline 默认),或问"<name> 怎么用"。

Read the full file on GitHub · 108 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. 9d ago Changed · +1 lines bf6560c3b972
  2. 10d ago Changed · +1 lines af21fb7ea6bf
  3. 24d ago Changed · +4 lines 20d33cbec114
  4. 28d ago Changed · +3 lines 82fbd38297d8
  5. 2mo ago First seen · 99 lines · 30 tokens per session scan A 0b68a8145138

Subscribe to this mod's changes

career-ops is a skill published in the GitHub repository shuheng-mo/career-ops-china (114 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 1,509 once invoked, about $0.0001 per session on Opus 5.5. 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.

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