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Agent Skill · 研究检索

job(工作)

job 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

job 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 10,960。

总安装 11,890周安装 481GitHub Stars 公开资料未说明下载 3,733核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:job(工作)
来源仓库:https://github.com/ethagent/job
安装命令:
openclaw skills install job
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install job

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

提供完整的求职情报与职业指导服务。覆盖职位搜索、简历优化与面试准备。输出个性化建议与行业趋势分析。job 属于研究检索类 Skill,可作为该场景下的辅助能力补充。需用户提供背景信息以定制方案。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。建议结合个人实际情况调整策略。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install job;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

job 怎么安装?

在终端执行 openclaw skills install job。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

job 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

job 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

job 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

job 用的人多吗?

公开数据是累计安装 11,890 次,近一周安装 481 次,下载 3,733 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

job 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
job

工作 · 本页

11,890—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
job
description
>

Job — Complete Job Search Intelligence System

What This Skill Does

A job search is a sales process where you are both the salesperson and the product. The candidate who understands this — who approaches their search with the same rigor, strategy, and persistence they would apply to any important professional project — finds better jobs faster and negotiates better outcomes than the candidate who submits applications and waits.

Most job searches fail not because the candidate is unqualified. They fail because the resume is not optimized for how it will be read, the applications are going to the wrong places, the interview preparation is generic rather than specific, and the negotiation is either skipped entirely or handled poorly.

This skill fixes all of that.


Core Principle

The job search has three phases that require completely different strategies: getting seen, getting selected, and getting the offer you deserve. Failing in any one phase produces the same outcome — no job — but requires a completely different fix. The skill diagnoses which phase is failing and applies the right intervention.


Workflow

Step 1: Assess the Job Search Situation

JOB_SEARCH_PHASES = {
  "getting_seen": {
    "symptom":   "Applying to many jobs, getting few or no responses",
    "causes":    ["Resume not passing ATS", "Wrong keywords", "Applying to wrong roles",
                  "Too broad or too narrow targeting"],
    "fix":       "Resume optimization, targeting strategy, network activation"
  },
  "getting_selected": {
    "symptom":   "Getting interviews but not advancing to next rounds",
    "causes":    ["Weak interview performance", "Poor story structure",
                  "Not researching company specifically", "Failing technical screens"],
    "fix":       "Interview preparation, story development, company research framework"
  },
  "getting_the_offer": {
    "symptom":   "Getting to final round but not receiving offers, or receiving low offers",
    "causes":    ["Reference issues", "Salary expectation mismatch", "Weak close",
                  "Poor negotiation"],
    "fix":       "Reference preparation, salary research, negotiation scripts"
  }
}

Step 2: Resume Architecture

RESUME_FRAMEWORK = {
  "ATS_optimization": {
    "how_ATS_works": """
      def ats_score(resume, job_description):
          resume_keywords = extract_keywords(resume)
          jd_keywords = extract_keywords(job_description)
          match_score = len(resume_keywords & jd_keywords) / len(jd_keywords)
          # Resumes scoring below 0.6-0.7 are filtered before human review
          return match_score
    """,
    "rules": [
      "Mirror exact language from job description — not synonyms",
      "Standard section headers: Experience, Education, Skills — not creative alternatives",
      "No tables, columns, headers/footers, or text boxes — ATS cannot parse them",
      "Submit as .docx or .pdf depending on instructions",
      "Spell out acronyms once: Search Engine Optimization (SEO)"
    ]
  },

  "structure": {
    "contact":      "Name, email, phone, LinkedIn, city/state — no full address needed",
    "summary":      "3 sentences: who you are professionally, your strongest value, what you want next",
    "experience":   "Reverse chronological. Each role: company, title, dates, 3-5 bullets.",
    "skills":       "Technical skills, tools, certifications — keywords for ATS",
    "education":    "After experience for anyone with 3+ years of work history"
  },

  "bullet_formula": {
    "structure":  "Action verb + what you did + measurable result",
    "examples": {
      "weak":   "Responsible for managing social media accounts",
      "strong": "Grew Instagram following from 8K to 47K in 14 months through
                 daily content strategy, increasing inbound leads by 34%"
    },
    "action_verbs": ["Led", "Built", "Drove", "Reduced", "Increased", "Launched",
                     "Negotiated", "Designed", "Implemented", "Managed", "Created"],
    "quantify_everything": "Numbers, percentages, dollar amounts, team sizes, timeframes"
  },

  "tailoring_per_application": """
    def tailor_resume(base_resume, job_description):
        jd_keywords = extract_top_keywords(job_description, n=15)
        required_skills = extract_requirements(job_description)

        for keyword in jd_keywords:
            if keyword not in base_resume:
                find_experience_that_demonstrates(keyword)
                rewrite_bullet_to_include(keyword)

        reorder_bullets_by_relevance_to(job_description)
        return tailored_resume
    # Time: 15-20 minutes per application. Worth it for roles you want.
  """
}

Step 3: Job Search Strategy

SEARCH_STRATEGY = {
  "targeting": {
    "define_clearly": {
      "role_titles":    "List 5-10 titles for the role you want — they vary by company",
      "company_types":  "Size, industry, stage, culture — be specific",
      "geography":      "In-office, hybrid, remote — know your constraints",
      "level":          "IC vs management, junior vs senior — match to your experience"
    },
    "target_company_list": {
      "size":     "50-100 target companies is manageable",
      "sources":  ["LinkedIn company search", "Industry lists", "Portfolio companies of VCs you know",
                   "Competitors of companies you know well"],
      "tracking": "Spreadsheet: Company | Role | Connection | Status | Next Action | Date"
    }
  },

  "channel_allocation": {
    "network":         "60-70% of jobs are filled through relationships — prioritize this",
    "direct_apply":    "Company career pages directly — better than aggregators",
    "recruiters":      "Valuable for senior roles — build relationships before you need them",
    "job_boards":      "LinkedIn, Indeed — high volume but low conversion, use as supplement",
    "principle":       "A warm introduction converts at 10x the rate of a cold application"
  },

  "networking_approach": {
    "informational_interview": {
      "purpose":   "Learn about a role or company, build relationship, get referred",
      "ask":       "20-minute call to learn about their experience at [company]",
      "never_ask": "Do you know of any openings — too transactional too early",
      "follow_up": "Thank you note within 24 hours. Stay in touch. Ask for one introduction."
    },

    "outreach_script": {
      "cold":    "Hi [name], I came across your work on [specific thing] and am exploring
                  roles in [area]. I would love 20 minutes to hear about your experience
                  at [company] — happy to work around your schedule.",
      "warm":    "Hi [name], [mutual connection] suggested I reach out. I am exploring
                  roles in [area] and would value 20 minutes of your perspective on [company/role]."
    }
  }
}

Step 4: Interview Excellence

INTERVIEW_FRAMEWORK = {
  "preparation_system": {
    "company_research": {
      "required": ["Business model and revenue sources",
                   "Recent news — last 3 months",
                   "Products and key competitors",
                   "Culture and values — Glassdoor, LinkedIn posts",
                   "Your interviewer's background — LinkedIn"],
      "use_in_interview": "Ask about something specific you researched — signals genuine interest"
    }
  },

  "story_bank": {
    "STAR_method": {
      "Situation": "Context — brief, specific, relevant",
      "Task":      "What you were responsible for",
      "Action":    "What YOU specifically did — not the team, not the process",
      "Result":    "Measurable outcome — numbers, percentages, business impact"
    },
    "stories_to_prepare": [
      "Greatest professional achievement",
      "Difficult challenge and how you overcame it",
      "Conflict with colleague and resolution",
      "Failed project and what you learned",
      "Time you led without authority",
      "Time you had to change someone's mind with data",
      "Time you had to make a decision with incomplete information"
    ]
  },

  "question_handling": {
    "tell_me_about_yourself": {
      "formula":  "Present → Past → Future",
      "structure": "I am currently [role] at [company] where I [key responsibility].
                    Before that [most relevant background]. I am looking for [specific next step]
                    because [genuine reason that connects to this role].",
      "length":   "90 seconds maximum"
    },
    "weakness_question": {
      "formula":  "Real weakness + what you have done about it + current state",
      "avoid":    "I work too hard. I am a perfectionist. — Interviewers have heard these 1000 times"
    },
    "salary_question": {
      "if_asked_early": "I am flexible — I would want to understand the full scope of the role
                          before discussing compensation. What is the budgeted range?",
      "if_pressed":     "Based on my research and experience, I am targeting [range].
                          Is that aligned with the budget for this role?"
    }
  },

  "questions_to_ask": {
    "about_role":    "What does success look like in the first 90 days",
    "about_team":    "How would you describe the team culture and how decisions get made",
    "about_company": "What is the biggest challenge the team is working through right now",
    "about_interviewer": "What has kept you at [company] — what do you find most energizing",
    "never_ask":     "What does the company do. How much vacation do I get. When will I be promoted."
  }
}

Step 5: Offer Evaluation and Negotiation

OFFER_FRAMEWORK = {
  "total_compensation_calculation": """
    def calculate_total_comp(offer):
        base = offer.base_salary
        bonus = base * offer.target_bonus_percent
        equity_annual = estimate_equity_value(offer.equity) / offer.vesting_years
        benefits_value = estimate_benefits(offer.health, offer.retirement_match, offer.pto)

        total = base + bonus + equity_annual + benefits_value
        return {
            "cash_comp":   base + bonus,
            "equity_comp": equity_annual,
            "benefits":    benefits_value,
            "total":       total
        }
    # Never compare offers on base salary alone
  """,

  "negotiation_framework": {
    "always_negotiate": "60% of employers expect negotiation. Not negotiating leaves money on table.",
    "opening_script":   "Thank you for the offer — I am genuinely excited about this opportunity.
                          I was hoping we could get to [target number]. Is there flexibility there?",
    "after_counter":    "Stay silent. Do not justify or elaborate. The discomfort is working for you.",
    "if_base_is_fixed": "If base is truly fixed, negotiate: signing bonus, extra PTO, remote days,
                          accelerated review date, equity refresh, professional development budget",
    "get_it_in_writing": "Verbal offers mean nothing. Do not resign current job until written offer signed."
  },

  "offer_decision_framework": {
    "evaluate_on": ["Compensation vs market rate",
                    "Role scope and growth trajectory",
                    "Manager quality — people leave managers not companies",
                    "Team and culture",
                    "Company trajectory — growing or shrinking",
                    "Mission alignment"],
    "red_flags":   ["Pressure to decide immediately",
                    "Vague role description that no one can clarify",
                    "High turnover in the team",
                    "Rescinded offers or changed terms at last minute"]
  }
}

Career Transition Support

CAREER_CHANGE_FRAMEWORK = {
  "transferable_skills_audit": {
    "principle": "Every skill has a transferable equivalent. The job is to translate it.",
    "example":   "Teaching → Training and Development, Curriculum Design, Public Speaking",
    "process":   "List everything you have done. Find the business language for each."
  },

  "bridge_building": {
    "education":   "Certifications and courses signal commitment to the new field",
    "projects":    "Build something in the new domain — portfolio beats credentials",
    "network":     "Join communities in the target field before you need a job in it",
    "adjacent_role": "Sometimes the fastest path is an adjacent role at current company"
  }
}

Quality Check Before Delivering

  • [ ] Job search phase correctly diagnosed — getting seen vs selected vs offer
  • [ ] Resume optimized for ATS with job-specific keywords
  • [ ] Bullet points follow action-result formula with quantification
  • [ ] Interview stories prepared in STAR format for key scenarios
  • [ ] Salary research completed before any negotiation guidance
  • [ ] Total compensation calculated including equity and benefits
  • [ ] Negotiation script specific to offer and situation
  • [ ] Red flags in offer or process flagged proactively

平台分布

OpenClaw

82.77%
按下载量换算3,090

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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