Token导航 LogoToken导航

Agent Skill · 研究检索

jobclaw-recruit(工作爪招募)

jobclaw-recruit 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。

jobclaw-recruit 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 6,887。

总安装 20,604周安装 876GitHub Stars 公开资料未说明下载 7,218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:jobclaw-recruit(工作爪招募)
来源仓库:https://github.com/imluyu/jobclaw-recruit
安装命令:
openclaw skills install jobclaw-recruit
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 jobclaw-recruit

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。

帮助招聘人员将职位发布到职位匹配系统。当用户想要执行以下操作时使用:(1) 发布职位,(2) 发布职位,(3) 雇用人员,(4) 招募候选人,(5) 寻找员工,或 (6) 发布职位空缺广告。支持灵活的信息收集 - 用户可以立即提供所有详细信息或逐步指导。自动创建招聘人员帐户、生成工作向量并启用人工智能驱动的候选人匹配。

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 jobclaw-recruit;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

jobclaw-recruit 怎么安装?

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

jobclaw-recruit 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。

jobclaw-recruit 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。

jobclaw-recruit 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。

jobclaw-recruit 用的人多吗?

公开数据是累计安装 20,604 次,近一周安装 876 次,下载 7,218 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。

jobclaw-recruit 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。

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
jobclaw-recruit

工作爪招募 · 本页

20,604—需要联网MIT-0有提醒

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
recruiter
description
Help recruiters publish job postings to the job matching system. Use when users want to: (1) post a job, (2) publish a position, (3) hire someone, (4) recruit candidates, (5) find employees, or (6) advertise job openings. Supports flexible information collection - users can provide all details at once or be guided through step-by-step. Automatically creates recruiter account, generates job vectors, and enables AI-powered candidate matching.

Recruiter

Publish, update, and manage job postings in the AI-powered job matching system, and view matched candidates.

Overview

This skill helps recruiters manage job postings through an interactive conversation. Provide information flexibly - share everything at once or answer questions step-by-step. The system supports:

  1. Publish job - Create a recruiter account, publish a job posting, and trigger AI matching
  2. Update job - Modify job details (title, requirements, salary, etc.)
  3. Delete job - Soft-delete job posting (mark as INACTIVE, preserving match history)
  4. View jobs - Check all your published jobs
  5. List matched candidates - View candidates matched by the AI system with similarity scores

Available Scripts

  • publish_job.py - Publish, update, delete jobs, and list matches for a specific job
  • get_profile.py - View all your jobs and matched candidates (read-only)

Workflow

Publish Job (action: publish)

Step 1: Gather Job Posting Information

Collect the following required fields. Users can provide them in any order or all at once:

Required fields:

  • Job title: Position name (e.g., "Senior Python Backend Engineer")
  • Company name: Employer name
  • Job requirements: Detailed requirements including skills, responsibilities, and qualifications
  • Salary range: Compensation range (e.g., "25k-40k", "30k-50k")
  • Work location: Office location (e.g., "Shanghai-Changning District", "Beijing-Chaoyang District")
  • Job type: Employment type (e.g., "Full-time", "Part-time", "Contract")
  • Education requirement: Minimum education level (e.g., "Bachelor's degree or above")
  • Experience requirement: Required years of experience (e.g., "3-5 years", "5+ years")

Example user inputs:

_All at once:_

"I want to post a job for a Python Backend Engineer at Pinduoduo in Shanghai Changning District. Salary 25k-40k. Requirements: Familiar with Python, Django/Flask frameworks, RESTful API development experience. Knowledge of MySQL, Redis databases. E-commerce or payment system experience preferred. Full-time position, bachelor's degree or above, 3-5 years experience."

_Step by step:_

"I need to hire a developer" [Claude asks for job title] "Python Backend Engineer" [Claude asks for company, requirements, salary, location, etc.]
Step 2: Validate Completeness

Before submission, verify all required fields are present. If any are missing, ask the user to provide them.

Step 3: Publish Job Posting
cat <<EOF | python3 scripts/publish_job.py
{
  "action": "publish",
  "title": "<job title>",
  "companyName": "<company name>",
  "requirement": "<detailed requirements>",
  "salary": "<salary range>",
  "location": "<work location>",
  "jobType": "<employment type>",
  "education": "<education requirement>",
  "experience": "<experience requirement>",
  "status": "ACTIVE"
}
EOF
Step 4: Confirm Success

After successful publication, inform the user and save the returned job ID for future operations (update, delete, list matches). The token is automatically saved.


Update Job (action: update)

Requires the jobId from a previous publish. Only changed fields need to be provided. The script will automatically use the saved token.

cat <<EOF | python3 scripts/publish_job.py
{
  "action": "update",
  "jobId": "<job id>",
  "salary": "<new salary range>",
  "requirement": "<updated requirements>"
}
EOF

Updatable fields: title, companyName, requirement, salary, location, jobType, education, experience, status.


Delete Job (action: delete)

Soft-deletes the job posting by marking it as INACTIVE. Match history is preserved.

cat <<EOF | python3 scripts/publish_job.py
{
  "action": "delete",
  "jobId": "<job id>"
}
EOF

View Jobs and Matches (get_profile.py)

Check your published jobs and matched candidates without making any changes.

View All Jobs
cat <<EOF | python3 scripts/get_profile.py
{
  "action": "jobs"
}
EOF
View Specific Job Details
cat <<EOF | python3 scripts/get_profile.py
{
  "action": "job",
  "jobId": "<job id>"
}
EOF
View Matches for Specific Job
cat <<EOF | python3 scripts/get_profile.py
{
  "action": "matches",
  "jobId": "<job id>"
}
EOF
View All Matches Across All Jobs
cat <<EOF | python3 scripts/get_profile.py
{
  "action": "all-matches"
}
EOF
View Full Information (all jobs + all matches)
cat <<EOF | python3 scripts/get_profile.py
{
  "action": "full"
}
EOF

When to use get_profile.py:

  • User asks "What jobs have I published?" or "Show me my jobs"
  • User wants to check matches across all jobs
  • User wants to review job details before updating
  • User asks "Do I have any candidates?"

List Matched Candidates (action: matches)

Retrieve candidates matched by the AI system for a specific job posting and provide comprehensive multi-dimensional analysis.

cat <<EOF | python3 scripts/publish_job.py
{
  "action": "matches",
  "jobId": "<job id>"
}
EOF
Step 1: Retrieve Matched Candidates

The API returns a list of matched candidates with similarity scores. Each match includes:

  • Candidate details (name, resume, skills, experience, etc.)
  • Similarity score (0-1 range, based on vector matching)
  • Match metadata
Step 2: Provide Comparative Summary

After analyzing individual candidates, provide a comparative summary:

Top 3 Recommendations: Rank the top 3 candidates with brief rationale for each.

Candidate Distribution:

  • Excellent matches (score > 0.85): X candidates
  • Good matches (score 0.75-0.85): Y candidates
  • Moderate matches (score 0.65-0.75): Z candidates

Hiring Strategy Advice:

  • Which candidates to prioritize for interviews
  • Suggested interview panel composition
  • Timeline recommendations
  • Backup candidate strategy
Output Format Guidelines

IMPORTANT: Always respond in the user's language. If the user communicates in Chinese, respond in Chinese. If in English, respond in English. Adapt all section headers, labels, and content to match the user's language.

Structure your analysis report as follows:

Report Header:

  • Title indicating this is a candidate match analysis report
  • Job position and company name
  • Visual separators (lines, emojis) to organize sections

For Each Matched Candidate:

  1. Candidate Header Section

- Candidate name/identifier and number - Visual separator line

  1. Overall Match Score (📈)

- Display the similarity score (e.g., 0.89) with interpretation (excellent/good/moderate/fair) - Brief summary of why this candidate matches or doesn't match

  1. Skill Alignment Analysis (🔧)

- ✅ List matching skills with experience levels - 💡 Highlight bonus skills (beyond requirements) - ⚠️ Identify skill gaps (required but missing) - Provide skill match percentage estimate

  1. Experience Fit Analysis (💼)

- Compare required vs. actual years of experience - Assess industry/domain experience relevance - Evaluate project complexity and scale alignment - Determine seniority level match - Review career progression trajectory

  1. Education & Qualifications (🎓)

- Education level match - Relevant certifications - Academic background relevance

  1. Cultural & Team Fit (🤝)

- Work style indicators from resume - Team collaboration experience - Leadership potential (if applicable) - Communication skills evidence

  1. Compensation Expectations (💰)

- Candidate's salary expectations vs. job offer - Negotiation room assessment - Total compensation considerations

  1. Advantages & Disadvantages (✅ ⚠️)

- List 3-5 key strengths of this candidate - List 2-4 potential concerns or gaps - Be objective and balanced

  1. Hiring Recommendation (🎯)

- Priority level: 🔥 High Priority / ⭐ Medium Priority / 💭 Consider - Recommended action with clear reasoning - Suggested interview focus areas - Onboarding considerations

  1. Interview Strategy (📝)

- Key areas to probe during interview - Technical assessment recommendations - Behavioral questions to ask - Red flags to watch for

  1. Retention & Growth Potential (🚀)

- Long-term fit assessment - Growth trajectory within the company - Retention risk factors - Development opportunities needed

After Individual Candidate Analysis:

Comparative Summary Section:

  1. Top 3 Recommendations (🏆)

- Rank top 3 candidates with medal emojis (🥇🥈🥉) - Brief rationale for each ranking

  1. Candidate Distribution (📈)

- Count of excellent matches (score > 0.85) - Count of good matches (score 0.75-0.85) - Count of moderate matches (score 0.65-0.75)

  1. Hiring Strategy Advice (💡)

- Which candidates to prioritize for interviews - Suggested interview panel composition - Timeline recommendations - Backup candidate strategy - Risk mitigation strategies

  1. Action Checklist (🎯)

- Immediate next steps (contact candidates, schedule interviews) - Preparation tasks (interview questions, evaluation criteria) - Budget/compensation considerations - Process setup (offer templates, onboarding plans)

Formatting Guidelines:

  • Use emojis to make sections visually distinct
  • Use bullet points and numbered lists for clarity
  • Include visual separators (━━━) between major sections
  • Keep language professional and objective
  • Be specific and actionable in all recommendations
  • Balance honesty about gaps with recognition of potential
Important Notes
  • Always provide detailed analysis: Don't just list candidates with scores. Hiring managers need actionable insights.
  • Be objective about gaps: Help identify areas where candidates might need support or training.
  • Consider total value: Match score is just one factor; potential, cultural fit, and long-term growth matter too.
  • Prioritize actionability: Every analysis should lead to clear hiring decisions and interview strategies.
  • Personalize recommendations: Reference specific details from the job requirements in your analysis.
  • Think long-term: Consider not just immediate fit, but retention and growth potential.

API Configuration

Default API endpoint: https://api.jobclaw.ai

To use a different endpoint, modify the apiUrl parameter when calling the script.

Error Handling

If any operation fails:

  • Check if the API server is running
  • Verify all required fields are provided
  • Ensure the API endpoint is correct
  • For update/delete/matches: ensure a valid jobId is provided
  • Review the error message and guide the user accordingly

Resources

scripts/publish_job.py

Python script supporting four actions (publish, update, delete, matches):

  • Creating new recruiter accounts (auto-created on publish)
  • Publishing and updating job postings
  • Soft-deleting job postings (mark INACTIVE)
  • Listing AI-matched candidates

The script uses Python's built-in urllib library (no external dependencies required).

平台分布

OpenClaw

79.79%
按下载量换算5,759

安全审计

VirusTotal

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills