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hr小时

Agent Skill

hr 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

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下载量

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:hr(小时)
来源仓库:https://github.com/agenticio/hr
安装命令:
openclaw skills install hr
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 hr

简介

为创始人与 HR 专业人员提供全周期人力资源情报支持。

  • 覆盖招聘、入职、绩效管理等核心业务流程的智能辅助。
  • 可根据输入需求自动生成岗位描述、评估表或合规政策草案。
  • 涉及员工隐私数据时应严格遵守相关法律法规要求。hr 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 建议定期更新知识库以保持政策时效性与地域适应性。

SKILL.md

name
hr
description
>

HR — Complete Human Resources Intelligence System

What This Skill Does

The people decisions in an organization compound faster than almost any other decisions. A great hire in a critical role returns ten times their cost in the first year. A bad hire in the same role costs twice their salary in direct costs and multiples of that in organizational drag, team morale, and founder time. Getting people decisions right is not an HR function — it is a strategy function.

This skill treats it that way.


Core Principle

HR systems exist to help people do their best work and to protect the organization when they do not. The organizations that build these systems thoughtfully — before they need them — have an enormous advantage over those that build them reactively in response to problems they could have prevented.


Workflow

Step 1: Identify the HR Scenario

HR_SCENARIOS = {
  "hiring": {
    "stages":    ["role_definition", "job_description", "sourcing", "screening",
                  "interviewing", "assessment", "offer", "negotiation"],
    "key_risk":  "Hiring for the wrong role definition is the most expensive hiring mistake"
  },
  "onboarding": {
    "stages":    ["pre_start", "day_one", "first_week", "30_60_90_day"],
    "key_risk":  "Poor onboarding doubles time to productivity and increases early attrition"
  },
  "performance": {
    "stages":    ["goal_setting", "regular_feedback", "formal_review", "PIP", "exit"],
    "key_risk":  "Delayed feedback turns fixable problems into terminations"
  },
  "compensation": {
    "components": ["base", "bonus", "equity", "benefits", "non_monetary"],
    "key_risk":   "Below-market compensation is invisible until your best people leave"
  },
  "termination": {
    "types":     ["performance", "redundancy", "misconduct", "mutual_agreement"],
    "key_risk":  "Procedural errors in termination create legal liability regardless of merit"
  },
  "compliance": {
    "areas":     ["employment_contracts", "leave_entitlements", "workplace_safety",
                  "discrimination", "privacy", "wage_and_hour"],
    "key_risk":  "Employment law violations are expensive and reputationally damaging"
  }
}

Step 2: Hiring Intelligence

HIRING_FRAMEWORK = {
  "role_definition": {
    "before_writing_JD": [
      "What problem does this role solve that is not currently being solved",
      "What does success look like in 90 days, 6 months, and 2 years",
      "What skills are truly required versus nice to have",
      "What type of person thrives in this team and culture",
      "Is this definitely a hire or could it be a tool, contractor, or process change"
    ]
  },

  "job_description_structure": {
    "title":         "Accurate to market — affects who applies and at what salary expectation",
    "about_company": "2-3 sentences. What you do and why it matters. No fluff.",
    "role_summary":  "What this person will own and what impact they will have",
    "responsibilities": "What they will actually do — specific verbs, not vague categories",
    "requirements":  {
      "must_have":   "Skills without which the person cannot do the job",
      "nice_to_have": "Skills that would accelerate their contribution",
      "rule":        "Every requirement must be genuinely necessary — credential inflation
                       screens out strong candidates and reduces diversity"
    },
    "compensation":  "Include range — job posts with salary ranges get 30% more applicants",
    "tone":          "Write for the candidate you want to attract, not the job spec lawyer"
  },

  "interview_framework": {
    "structured_interviews": {
      "principle": "Same questions in same order for all candidates — reduces bias, improves comparison",
      "question_types": {
        "behavioral": "Tell me about a time when — reveals actual past behavior",
        "situational": "What would you do if — reveals thinking and values",
        "technical":   "Demonstrate or solve — reveals actual skill level",
        "motivational": "Why this role, why now — reveals fit and retention risk"
      }
    },

    "evaluation_framework": """
      def evaluate_candidate(interview_notes):
          score_on = {
              "skill_match":      rate(1-5),  # Can they do the job
              "culture_add":      rate(1-5),  # Will they make the team better
              "motivation":       rate(1-5),  # Do they genuinely want this specifically
              "growth_potential": rate(1-5),  # Can they grow with the role
              "reference_signal": rate(1-5)   # What did references actually say
          }
          return {
              "hire":        all(v >= 3 for v in score_on.values()),
              "strong_hire": all(v >= 4 for v in score_on.values()),
              "no_hire":     any(v <= 2 for v in score_on.values())
          }
    """
  }
}

Step 3: Performance Management

PERFORMANCE_FRAMEWORK = {
  "goal_setting": {
    "OKR_structure": {
      "objective":     "Qualitative, inspiring, direction-setting",
      "key_results":   "3-5 measurable outcomes that define objective achievement",
      "principle":     "Key Results must be measurable. If you cannot measure it, it is not a KR."
    },
    "review_cadence": "Weekly 1:1s for real-time feedback. Monthly check-ins for goal tracking.
                       Quarterly formal reviews. Annual compensation review."
  },

  "feedback_delivery": {
    "SBI_framework": {
      "Situation":  "Specific context where the behavior occurred",
      "Behavior":   "Observable action — not interpretation, not character",
      "Impact":     "Concrete effect of the behavior on work, team, or outcomes"
    },
    "rules": ["Specific beats general always",
               "Immediate beats delayed — feedback loses value with time",
               "Private for criticism, public for praise",
               "Balanced feedback includes both what to continue and what to change"],
    "what_not_to_say": ["You always...", "You never...", "Your attitude is...",
                         "Everyone thinks...", "You should be more like..."]
  },

  "performance_improvement": {
    "PIP_principles": [
      "A PIP should be a genuine attempt to help the person succeed — not documentation for termination",
      "Specific, measurable performance standards that are achievable",
      "Regular check-ins during the PIP period",
      "Support and resources to address the gap",
      "Clear consequence if standards are not met"
    ],
    "PIP_structure": {
      "current_performance": "Specific examples of where performance falls short",
      "expected_standard":   "Exactly what good looks like, measured how",
      "support_provided":    "What the company will do to help",
      "timeline":            "Specific dates for review",
      "consequence":         "What happens if standard is not met"
    }
  }
}

Step 4: Compensation Architecture

COMPENSATION_FRAMEWORK = {
  "market_benchmarking": {
    "sources":    ["Levels.fyi for tech", "Glassdoor", "LinkedIn Salary",
                   "Industry surveys", "Recruiter conversations"],
    "principle":  "Pay at or above market for roles critical to your success.
                   Below-market compensation is an invisible tax you pay in attrition."
  },

  "pay_bands": {
    "purpose":    "Defined ranges for each role level — enables fair, consistent decisions",
    "structure":  "Minimum (entry for role) — Midpoint (fully proficient) — Maximum (top of range)",
    "rule":       "If someone is above the maximum, they have grown beyond the role — promote or accept flight risk"
  },

  "equity_principles": {
    "early_stage": "Options are the deferred compensation that makes below-market base viable",
    "cliff":       "Standard: 1-year cliff before any vesting begins",
    "vesting":     "Standard: 4-year vest with monthly vesting after cliff",
    "refreshers":  "Top performers need new grants to maintain retention incentive"
  }
}

Step 5: Termination Protocol

TERMINATION_FRAMEWORK = {
  "before_termination": {
    "documentation_required": [
      "Performance issues communicated in writing with dates",
      "Feedback given and documented",
      "PIP completed if performance-based termination",
      "HR or legal review completed",
      "Final decision maker aligned"
    ],
    "legal_review":   "Employment law is jurisdiction-specific. Review before any termination."
  },

  "the_conversation": {
    "timing":     "Monday or Tuesday morning — not Friday. Gives person time to take action.",
    "location":   "Private. In person where possible.",
    "duration":   "15-20 minutes maximum. Decision is made and not reversible.",
    "script":     {
      "opening":  "This is a difficult conversation. [Name], we have decided to end your employment.",
      "reason":   "State reason clearly and briefly. No lengthy justification.",
      "logistics": "Cover: last day, pay, benefits continuation, reference policy, equipment return",
      "closing":  "Dignified. Brief. Do not extend."
    },
    "what_not_to_do": ["Apologize repeatedly", "Argue or debate", "Give false hope",
                        "Over-explain", "Be surprised by emotional reaction"]
  },

  "post_termination": {
    "immediate":  ["Access revoked same day", "Equipment returned", "Team notified with appropriate explanation"],
    "severance":  "Consult legal on requirements. Voluntary severance above legal minimum often reduces risk.",
    "reference":  "Establish reference policy before you are asked — typically title, dates, eligibility for rehire only"
  }
}

Employment Law Principles

LEGAL_PRINCIPLES = {
  "employment_contracts": "Written contracts protect both parties. Verbal agreements are enforceable
                           but expensive to prove.",
  "at_will_vs_notice":    "At-will employment (US) differs significantly from notice period
                           requirements elsewhere — know your jurisdiction.",
  "protected_classes":    "Termination, discipline, and hiring decisions must never be based on
                           protected characteristics — race, gender, age, religion, disability,
                           and others vary by jurisdiction.",
  "wage_and_hour":        "Overtime rules, minimum wage, and classification of employees vs
                           contractors are heavily regulated with significant penalties for violations.",
  "disclaimer":           "Employment law is highly jurisdiction-specific and changes frequently.
                           HR decisions with legal exposure should be reviewed by employment counsel."
}

Quality Check Before Delivering

  • [ ] Jurisdiction flagged — employment law varies significantly by location
  • [ ] Role definition completed before job description drafted
  • [ ] Interview questions are structured and behavioral
  • [ ] Performance feedback follows SBI or equivalent specific framework
  • [ ] PIP includes measurable standards and genuine support
  • [ ] Termination documentation is complete before conversation happens
  • [ ] Legal review recommended for any termination or discrimination-adjacent scenario

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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96.45%
按下载量换算9,417

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只读

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安装前确认

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