boss-job-search

agentbay-ai/agentbay-skills · updated Jun 2, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/agentbay-ai/agentbay-skills --skill boss-job-search
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summary

在使用此技能之前,请确保已安装必要的依赖包:

skill.md

Boss直聘职位搜索

依赖

python3 -m pip install wuying-agentbay-sdk

安装步骤

在使用此技能之前,请确保已安装必要的依赖包:

python3 -m pip install wuying-agentbay-sdk

使用场景

  • 用户想搜索Boss直聘上的特定职位
  • 用户想筛选特定公司规模的岗位
  • 用户想了解某类职位的薪资范围和要求
  • 用户想获取最新的职位招聘信息

使用方法

python3 scripts/browser-use.py "<任务执行步骤>"

快速示例

示例1:搜索AI Infra工程师职位(公司规模10000人以上)

python3 scripts/browser-use.py " \
1. 前往Boss直聘网站 https://www.zhipin.com/ \
2. 等待页面加载完成,确认首页搜索框及导航栏显示正常 \
3. 定位顶部职位搜索框,输入关键词'AI Infra工程师' \
4. 点击搜索按钮(标注'搜索'或放大镜图标),进入职位列表页 \
5. 定位页面左侧筛选栏'公司规模'选项,展开下拉列表 \
6. 勾选'10000人以上'(若存在'10000人及以上'选项则勾选对应项) \
7. 等待页面自动刷新,筛选出符合公司规模条件的职位 \
8. 遍历前15条职位信息(若不足15条则获取全部) \
9. 提取每条职位的:职位名称、公司名称、公司规模、薪资范围、工作地点、职位发布时间、职位简介 \
10. 以markdown格式返回所有符合条件的职位信息
"

示例2:搜索Python工程师职位(不限公司规模)

python3 scripts/browser-use.py " \
1. 访问Boss直聘 https://www.zhipin.com/ \
2. 在搜索框中输入'Python工程师' \
3. 点击搜索进入职位列表页 \
4. 提取前10条职位的详细信息 \
5. 以markdown格式整理返回
"

示例3:搜索产品经理职位(筛选薪资和经验)

python3 scripts/browser-use.py " \
1. 打开Boss直聘网站 https://www.zhipin.com/ \
2. 搜索'产品经理' \
3. 在筛选栏中选择薪资范围'20-40K' \
4. 在筛选栏中选择经验要求'3-5年' \
5. 提取前15条符合条件的职位信息 \
6. 返回markdown格式的职位列表
"

输出格式

## Boss直聘职位搜索 - [搜索关键词]

### 职位列表

1. **职位名称**
   - 公司名称: xxx
   - 公司规模: xxx人
   - 薪资范围: xx-xxK
   - 工作地点: xxx
   - 发布时间: xxxx-xx-xx
   - 职位简介: xxxxx

2. **职位名称**
   - 公司名称: xxx
   - 公司规模: xxx人
   - 薪资范围: xx-xxK
   - 工作地点: xxx
   - 发布时间: xxxx-xx-xx
   - 职位简介: xxxxx

### 统计信息
- 总计: xx条职位
- 平均薪资: xx-xxK
- 最高薪资: xxK
- 最低薪资: xxK

异常处理

  • 若搜索关键词无匹配职位,反馈"无相关职位",终止任务
  • 若筛选栏选项不可选或页面异常,记录异常信息,尝试刷新页面后重试
  • 若页面出现验证码,提示需要人工协助验证,暂停任务
  • 若页面加载超时,增加等待时间或重新访问

注意事项

  • 始终注明信息来源为Boss直聘
  • 不需要创建新的脚本,用skill目录下的browser-use.py
  • 如果页面加载较慢,请耐心等待
  • 任务执行需要1~2分钟,请耐心等待观察,也不要重试
  • skill调用后,控制台会打印出asp流化链接(可视化的url),可告知用户查看
  • 职位信息会实时更新,以抓取时刻的数据为准
  • 部分职位详情可能需要登录才能查看完整信息
  • Boss直聘可能有反爬虫机制,遇到验证码请人工协助
how to use boss-job-search

How to use boss-job-search on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add boss-job-search
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/agentbay-ai/agentbay-skills --skill boss-job-search

The skills CLI fetches boss-job-search from GitHub repository agentbay-ai/agentbay-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/boss-job-search

Reload or restart Cursor to activate boss-job-search. Access the skill through slash commands (e.g., /boss-job-search) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.675 reviews
  • Chaitanya Patil· Dec 28, 2024

    boss-job-search reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Mateo Ndlovu· Dec 28, 2024

    boss-job-search has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Harper Ndlovu· Dec 28, 2024

    We added boss-job-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Yusuf Taylor· Dec 28, 2024

    Solid pick for teams standardizing on skills: boss-job-search is focused, and the summary matches what you get after install.

  • Arya Ramirez· Dec 24, 2024

    I recommend boss-job-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kwame Gonzalez· Dec 20, 2024

    boss-job-search has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ama Kapoor· Dec 16, 2024

    Useful defaults in boss-job-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Piyush G· Nov 19, 2024

    I recommend boss-job-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Valentina Wang· Nov 19, 2024

    boss-job-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Noah Wang· Nov 19, 2024

    Solid pick for teams standardizing on skills: boss-job-search is focused, and the summary matches what you get after install.

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