Job Hunter

AI-powered LinkedIn job search assistant that scrapes real-time listings, filters by technology and location, and scores each match — delivered through chat.

Setup

Before first use, the user needs a Google Gemini API key for AI scoring. Ask for it and save it:

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If the user doesn't have one, searches still work but without AI scoring (all jobs get a neutral 0.5 score). Free keys available at https://aistudio.google.com/apikey

Core Workflow

1. Conversational Search

When the user asks to search for jobs, gather these parameters conversationally:

• - keywords (required): job title or search terms (e.g., "Python developer", "data engineer")
• technologies (optional): required tech stack (e.g., ["Python", "AWS", "Docker"])
• countries (optional): countries to search in (e.g., ["Spain", "Germany"])
• remote (optional): true/false for remote-only jobs
• experience (optional): "entry", "mid", "senior", "director", "executive"
• exclude (optional): terms to exclude (e.g., ["consultant", "staffing"])
• companysize (optional): LinkedIn size codes "1"-"8" (1=1-10, 4=201-500, 7=5001-10000)
• salarymin (optional): minimum salary in EUR
• aiprompt (optional): extra criteria for AI scoring (e.g., "Must use microservices")
• maxpages (optional): pages to scrape per location (default 3, max 5)
• min_score (optional): minimum AI score to show (default 0.6)

Don't ask for ALL parameters — just ask the essentials (keywords, technologies, countries) and use sensible defaults for the rest. Let the user add filters if they want.

2. Run the Search

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The script returns JSON with scored jobs. Present the results in a clean format:

1. Senior Python Engineer — TechCorp
Madrid, Spain | Remote | €50k-60k
Score: 0.92 — "Excelente match: remoto, Python/FastAPI"
https://linkedin.com/jobs/view/12345

Show the top results (score >= min_score) sorted by score. If there are many results, show the top 10 and mention how many more are available.

Important: Searches take time (30-90 seconds) due to LinkedIn scraping. Tell the user to wait.

3. Save Interesting Jobs

Users can save jobs they like for later review:

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4. Search History

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Handling Different Languages

Detect the user's language and:

• - Respond in their language
• AI summaries are always in the user's language (pass it in ai_prompt, e.g., "Respond in Spanish")
• Job data stays in the original LinkedIn language

Tips

• - Per-country searches give much better results than global "Remote" searches on LinkedIn
• If no results, suggest broadening: fewer technologies, more countries, lower experience level
• LinkedIn may rate-limit after many searches — suggest waiting 5-10 minutes if errors occur
• Encourage users to save interesting jobs before they disappear from LinkedIn

Storage

All data stored as JSON in ~/.openclaw/job-hunter/:

• - config.json — Gemini API key and settings
• INLINECODE2 — search history
• INLINECODE3 — saved jobs

See references/search_format.md for full schemas.