什么是 Job Hunter？

Job Hunter 是 Openclaw Skills 生态系统中的一个先进技术模块，旨在管理整个就业搜索生命周期。它作为一个数字职业代理，通过利用自动化搜索脚本和数据驱动的候选人匹配，弥合了原始职位列表与成功面试之间的差距。

该技能使专业人士能够保持持续、高质量的搜索存在，而无需手动浏览招聘网站。通过将 LinkedIn、Indeed 和 Glassdoor 数据与个性化个人资料相结合，Job Hunter 提供了市场情报和申请定制服务，显著增加了获得目标职位的机会。

下载入口:https://github.com/openclaw/skills/tree/main/skills/sharbelayy/job-hunter

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

Job Hunter 应用场景

• 自动化发现多个全球平台上的新职位发布。
• 根据特定候选人个人资料对职位描述进行评分，以确定最佳匹配。
• 生成高度定制的求职信，将技能映射到特定的职位要求。
• 进行深入的薪资研究和当地市场趋势分析。
• 使用 STAR 法则故事脚本准备技术和行为面试。

1. 该技能首先在 profile.json 中定义候选人个人资料，捕获技能、资历和偏好。
2. 使用命令行脚本或 Web 工具执行自动化搜索策略，以汇总来自各大招聘网站的数据。
3. 每个识别出的机会都会通过适配分析引擎处理，计算基于百分比的匹配分数。
4. 整理后的结果通过每日简报呈现给用户，突出显示获准的机会和特定的技能差距。
5. 选择后，代理会通过起草定制文档和提供面试谈话要点来协助申请阶段。

Job Hunter 配置指南

要开始使用此 Openclaw Skills 扩展，请按照以下步骤操作：

1. 初始化您的候选人个人资料：

cp ./references/profile-template.json ./profile.json

2. 搜索您的目标职位：

./scripts/search_jobs.sh "Senior Developer" --location "Berlin" --days 5

3. 运行自动化适配分析脚本：

python3 ./scripts/analyze_fit.py --profile profile.json --jobs jobs.json --threshold 60

Job Hunter 数据架构与分类体系

该技能维护结构化的数据层次结构以跟踪进度：

name: job-hunter
description: Comprehensive job search assistant for finding, evaluating, and applying to job opportunities. Use when a user needs help with job hunting, job searching, finding openings, evaluating job fit, preparing applications, writing cover letters, interview preparation, salary research, or tracking applications. Supports multi-source job search across LinkedIn, Indeed, Glassdoor, and more with automated fit scoring against a candidate profile.

Job Hunter

End-to-end job search assistant — from finding opportunities to landing interviews.

Quick Start

1. Set up candidate profile

Create a profile JSON for the user. Use the template at {baseDir}/references/profile-template.json as a starting point. Ask the user about:

• Target roles and seniority level
• Key skills and tools
• Location preferences (cities + remote)
• Salary expectations
• Dealbreakers and excluded companies
• Preferred industries/domains

Save as profile.json in the workspace.

2. Search for jobs

Use the web_search tool with multiple queries to cast a wide net:

site:linkedin.com/jobs "[role]" "[city]"
site:indeed.com "[role]" "[city]"  
site:glassdoor.com/job "[role]" "[city]"
"[role]" "[city]" hiring 2025 2026

Expand keywords — don't just search one title. See {baseDir}/references/search-strategies.md for keyword expansion patterns.

Alternative: run the search script if Brave API is available:

{baseDir}/scripts/search_jobs.sh "CX Manager" --location "Amsterdam" --days 7

3. Evaluate fit

For each job found, run fit analysis:

python3 {baseDir}/scripts/analyze_fit.py --profile profile.json --jobs jobs.json --threshold 50

Or evaluate manually using this framework:

• Skill match (40%): Does user have 60%+ of required skills?
• Seniority match (25%): Right level — not over/under qualified?
• Location match (15%): Compatible location or remote?
• Domain match (10%): Preferred industry/domain?
• Red flags (10%): Excluded companies? Dealbreakers?

Score: ?? 75+ great | ?? 55-74 good | ?? 40-54 stretch | ?? <40 skip

4. Present results

For each job, present:

• Role & Company with direct link
• Fit score with color indicator
• Why it's a match (top 3 skill matches)
• Gaps to address (missing skills to highlight as "eager to learn")
• Salary estimate if available
• Recommendation: Apply / Maybe / Skip

Application Support

Cover letters

Read {baseDir}/references/cover-letter-guide.md for structure and tone guidelines. Generate tailored cover letters that:

• Reference specific company details (not generic)
• Map user's experience to top 2-3 job requirements
• Include quantified achievements
• Stay under 350 words

Interview prep

Read {baseDir}/references/interview-prep.md for complete preparation framework. Help with:

• Company research summaries
• STAR stories for key requirements
• Tailored "tell me about yourself" script
• Salary negotiation talking points
• Questions to ask the interviewer

Salary research

bash {baseDir}/scripts/salary_research.sh "Job Title" "Location"

Cross-reference 3+ sources. In the Netherlands: factor in 8% holiday allowance, possible 13th month, pension.

Daily Brief Format

When running as a scheduled job search brief:

1. New opportunities — jobs found in last 24h with fit scores and direct links
2. Application status — updates on pending applications
3. Action items — what to apply to today, follow-ups due
4. Market intel — industry trends, salary movements, hiring patterns

Tracking

Maintain a job tracker with:

• Company, role, date found, source URL
• Fit score and recommendation
• Status: new → applied → screening → interview → offer/rejected/ghosted
• Applied/skipped with reason
• Contact info and follow-up dates

Tips for Agents

• Never apply on behalf of the user — present opportunities, let them decide
• Don't overwhelm — 3-5 quality matches beat 20 mediocre ones
• Track excluded companies — never suggest the same company twice after rejection
• Be honest about fit — stretches are okay to flag, but don't oversell poor matches
• Respect dealbreakers — if user said no customer service, don't suggest it even if "it's a great company"
• Update the profile — as you learn user preferences, refine the profile
• Celebrate wins — applied to a job? Got an interview? Acknowledge it