Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Communication & Collaboration
Jobclaw Recruit
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.
skill openclawclawhub Free
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.
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Package facts
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- Manual review
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/publish_job.py, scripts/base.py, scripts/get_profile.py
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- imluyu
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Documentation
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: Publish job - Create a recruiter account, publish a job posting, and trigger AI matching Update job - Modify job details (title, requirements, salary, etc.) Delete job - Soft-delete job posting (mark as INACTIVE, preserving match history) View jobs - Check all your published jobs 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)
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: Candidate Header Section Candidate name/identifier and number Visual separator line Overall Match Score (๐) 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 Skill Alignment Analysis (๐ง) โ List matching skills with experience levels ๐ก Highlight bonus skills (beyond requirements) โ ๏ธ Identify skill gaps (required but missing) Provide skill match percentage estimate Experience Fit Analysis (๐ผ) 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 Education & Qualifications (๐) Education level match Relevant certifications Academic background relevance Cultural & Team Fit (๐ค) Work style indicators from resume Team collaboration experience Leadership potential (if applicable) Communication skills evidence Compensation Expectations (๐ฐ) Candidate's salary expectations vs. job offer Negotiation room assessment Total compensation considerations Advantages & Disadvantages (โ โ ๏ธ) List 3-5 key strengths of this candidate List 2-4 potential concerns or gaps Be objective and balanced Hiring Recommendation (๐ฏ) Priority level: ๐ฅ High Priority / โญ Medium Priority / ๐ญ Consider Recommended action with clear reasoning Suggested interview focus areas Onboarding considerations Interview Strategy (๐) Key areas to probe during interview Technical assessment recommendations Behavioral questions to ask Red flags to watch for Retention & Growth Potential (๐) Long-term fit assessment Growth trajectory within the company Retention risk factors Development opportunities needed After Individual Candidate Analysis: Comparative Summary Section: Top 3 Recommendations (๐) Rank top 3 candidates with medal emojis (๐ฅ๐ฅ๐ฅ) Brief rationale for each ranking Candidate Distribution (๐) 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) Hiring Strategy Advice (๐ก) Which candidates to prioritize for interviews Suggested interview panel composition Timeline recommendations Backup candidate strategy Risk mitigation strategies Action Checklist (๐ฏ) 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 (โโโ) 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
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).
Category context
Messaging, meetings, inboxes, CRM, and teammate communication surfaces.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Scripts1 Docs
- SKILL.md
- scripts/base.py
- scripts/get_profile.py
- scripts/publish_job.py