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. 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

• - publishjob.py - Publish, update, delete jobs, and list matches for a specific job
• getprofile.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

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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.

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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.

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

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Delete Job (action: delete)

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

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View Jobs and Matches (get_profile.py)

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

View All Jobs

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View Specific Job Details

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View Matches for Specific Job

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View All Matches Across All Jobs

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View Full Information (all jobs + all matches)

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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?"

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List Matched Candidates (action: matches)

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

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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. 1. Candidate Header Section

- Candidate name/identifier and number - Visual separator line

1. 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

1. 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

1. 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

1. 5. Education & Qualifications (🎓)

- Education level match - Relevant certifications - Academic background relevance

1. 6. Cultural & Team Fit (🤝)

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

1. 7. Compensation Expectations (💰)

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

1. 8. Advantages & Disadvantages (✅ ⚠️)

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

1. 9. Hiring Recommendation (🎯)

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

1. 10. Interview Strategy (📝)

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

1. 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. 1. Top 3 Recommendations (🏆)

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

1. 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)

1. 3. Hiring Strategy Advice (💡)

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

1. 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.

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API Configuration

Default API endpoint: INLINECODE9

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).