recruiter

# 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 ```bash 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. ```bash 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. ```bash 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 ```bash cat <<EOF | python3 scripts/get_profile.py { "action": "jobs" } EOF ``` #### View Specific Job Details ```bash cat <<EOF | python3 scripts/get_profile.py { "action": "job", "jobId": "<job id>" } EOF ``` #### View Matches for Specific Job ```bash cat <<EOF | python3 scripts/get_profile.py { "action": "matches", "jobId": "<job id>" } EOF ``` #### View All Matches Across All Jobs ```bash cat <<EOF | python3 scripts/get_profile.py { "action": "all-matches" } EOF ``` #### View Full Information (all jobs + all matches) ```bash 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. ```bash 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 2. **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 3. **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 4. **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 5. **Education & Qualifications** (🎓) - Education level match - Relevant certifications - Academic background relevance 6. **Cultural & Team Fit** (🤝) - Work style indicators from resume - Team collaboration experience - Leadership potential (if applicable) - Communication skills evidence 7. **Compensation Expectations** (💰) - Candidate's salary expectations vs. job offer - Negotiation room assessment - Total compensation considerations 8. **Advantages & Disadvantages** (✅ ⚠️) - List 3-5 key strengths of this candidate - List 2-4 potential concerns or gaps - Be objective and balanced 9. **Hiring Recommendation** (🎯) - Priority level: 🔥 High Priority / ⭐ Medium Priority / 💭 Consider - Recommended action with clear reasoning - Suggested interview focus areas - Onboarding considerations 10. **Interview Strategy** (📝) - Key areas to probe during interview - Technical assessment recommendations - Behavioral questions to ask - Red flags to watch for 11. **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 2. **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) 3. **Hiring Strategy Advice** (💡) - Which candidates to prioritize for interviews - Suggested interview panel composition - Timeline recommendations - Backup candidate strategy - Risk mitigation strategies 4. **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).