Job Hunter

Build and deploy an automated job hunting system with Telegram bot. Scrapes LinkedIn jobs, scores them by match percentage, sends notifications with apply buttons, and generates tailored CVs. Use when: setting up job search automation, building a job-matching bot, creating a Telegram-based job alert system, helping someone find a job automatically. Triggers: 'job search bot', 'automated job hunting', 'find jobs for', 'job alert system', 'build job bot'.

barleviatias@barleviatias

Install

openclaw skills install @barleviatias/job-hunter-bot

Job Hunter - Automated Job Search System

Build a complete job hunting system: LinkedIn scraper, match scorer, and Telegram bot with inline buttons.

What This System Does

Scrapes real jobs from LinkedIn (public guest API, no login needed)
Scores each job 0-100% based on candidate profile (title, skills, experience, location)
Sends matching jobs to Telegram with action buttons (details, apply, remove)
Provides a clean foundation you can extend with CV generation later if needed

Setup Flow

1. Gather Candidate Profile

Ask the user for:

Target roles (e.g. data analyst, BI developer, frontend developer)
Core skills (e.g. SQL, Python, React, Power BI)
Bonus skills (nice-to-have)
Max years of experience they qualify for
Preferred location and metro area cities
Contact info (name, email, phone, LinkedIn URL)
Work experience (companies, roles, dates, bullet points)
Education (degree, institution, year)

2. Create Telegram Bot

Guide the user:

Open Telegram, search for @BotFather
Send /newbot, choose a name and username
Copy the bot token
Get their Telegram user ID (send a message to @userinfobot)
Optionally add more authorized users (e.g. the job seeker)

3. Deploy the System

Create a project directory and deploy these scripts (from scripts/):

text

job-hunter/
├── config.json          # Bot token, user IDs, candidate profile
├── jobs.db              # SQLite database (auto-created)
├── scorer.py            # Match scoring engine
├── linkedin_scraper.py  # LinkedIn job scraper
├── bot.py               # Telegram bot with inline buttons
└── notify_new_jobs.py   # Send new matches to Telegram

config.json Structure

json

{
  "telegram_bot_token": "TOKEN_FROM_BOTFATHER",
  "telegram_user_id": 123456789,
  "authorized_users": [123456789],
  "notify_users": [123456789],
  "candidate": {
    "name": "Full Name",
    "email": "email@example.com",
    "phone": "054-1234567",
    "linkedin": "linkedin.com/in/username",
    "location": "Tel Aviv, Israel",
    "target_titles": ["data analyst", "bi developer"],
    "good_titles": ["business analyst"],
    "core_skills": ["sql", "python", "power bi"],
    "bonus_skills": ["etl", "dax", "pandas"],
    "max_years": 2,
    "preferred_locations": ["tel aviv", "herzliya", "ramat gan"],
    "metro_locations": ["petah tikva", "rishon lezion"]
  }
}

4. Customize Scripts

After copying scripts from scripts/, customize:

scorer.py - Update PROFILE dict with candidate's profile from config.json
linkedin_scraper.py - Update DEFAULT_QUERIES with relevant search terms
bot.py - Should work with just config.json changes
notify_new_jobs.py - Verify notification flow and recipients

5. Install Dependencies

Install Python dependencies required by the included scripts. At minimum, verify the libraries imported by the scraper and bot are available in your environment.

6. Initialize Database

The database auto-creates on first run. Schema:

sql

CREATE TABLE jobs (
    job_id TEXT PRIMARY KEY,
    title TEXT, company TEXT, location TEXT,
    url TEXT, career_url TEXT,
    description TEXT, requirements TEXT,
    required_years INTEGER,
    published_date TEXT, found_date TEXT,
    status TEXT DEFAULT 'new'
);

7. Start the Bot

bash

nohup python3 -u bot.py > bot.log 2>&1 &

8. Set Up Daily Search (Cron)