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)

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:

Candidate Header Section
Candidate name/identifier and number
Visual separator line
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
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
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
Education & Qualifications (🎓)
Education level match
Relevant certifications
Academic background relevance
Cultural & Team Fit (🤝)
Work style indicators from resume
Team collaboration experience
Leadership potential (if applicable)
Communication skills evidence
Compensation Expectations (💰)
Candidate's salary expectations vs. job offer
Negotiation room assessment
Total compensation considerations
Advantages & Disadvantages (✅ ⚠️)
List 3-5 key strengths of this candidate
List 2-4 potential concerns or gaps
Be objective and balanced
Hiring Recommendation (🎯)
Priority level: 🔥 High Priority / ⭐ Medium Priority / 💭 Consider
Recommended action with clear reasoning
Suggested interview focus areas
Onboarding considerations
Interview Strategy (📝)
- Key areas to probe during interview
- Technical assessment recommendations
- Behavioral questions to ask
- Red flags to watch for
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:

Top 3 Recommendations (🏆)
Rank top 3 candidates with medal emojis (🥇🥈🥉)
Brief rationale for each ranking
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)
Hiring Strategy Advice (💡)
Which candidates to prioritize for interviews
Suggested interview panel composition
Timeline recommendations
Backup candidate strategy
Risk mitigation strategies
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).

jobclaw-recruit

Installation