remote-jobs-finder_skill

Overview

This skill is a conversational remote job finder powered by Remote Rocketship’s curated feed. It onboards users with a few natural-language questions, remembers preferences, and ranks results by best-fit or newest-first. It supports resume-based scoring, easy pagination (“send me 20 more”), and optional scheduled monitoring for new matches.

How this skill works

The skill asks brief onboarding questions (roles, location eligibility, must-haves/deal-breakers, optional resume, and monitoring cadence) and stores a simple profile in memory. It fetches jobs via Remote Rocketship tools, applies filter hygiene and optional resume scoring, then returns paginated results (default 20). If an API key is provided, the skill saves it securely and uses it for subsequent calls; scheduling creates cron checks that notify only on new jobs.

When to use it

• When you want help finding remote roles in natural language
• To browse or filter Remote Rocketship listings without using a dashboard
• When you want results ranked by best-fit or newest first
• To paginate results conversationally: “send me 20 more” / “next page”
• To set up ongoing checks (hourly, daily, etc.) and get notified about new matches

Best practices

• Answer the onboarding questions to improve match quality but you can skip any and still get results
• Provide an API key when prompted to enable full searches; paste it once and it will be saved (never echoed back)
• If you share a resume, it stays with the agent and is used locally for fit scoring only
• Use clear filter updates (e.g., “only contract roles”) so the page resets and a fresh search runs
• Ask for pagination explicitly (more / next / previous) and I’ll report ranges like “Showing 21–40 of 134”

Example use cases

• “Find me remote Product Manager roles in the UK and rank by best fit”
• “Show remote backend engineering jobs worldwide — send me 20 more”
• “Keep an eye out hourly for new design roles and message me only when something new appears”
• “I’ll paste my resume — rank results by fit and explain why each match is ranked”