apify-google-flights-dealslisted

Find genuine google flights deals from a home airport with the Apify Google Flights Deals API Actor (johnvc/google-flights-deals-api). Give one IATA code and get the thirty cheapest destinations back as rows, each carrying the fare, what that route typically costs, the saving between them, and an is_below_typical flag. That flag is the point, because a cheap fare and a good deal are different things, and most of a cheapest-first list is short-haul that is cheap because it is close, not because the price is unusual. There is no arrival airport, the feed answers where can I go cheaply rather than what does this route cost. Filter by stops, cabin, budget, or trip length. Use when the user wants flight deals, cheap flights from an airport, fare drop discovery, or destination inspiration priced against a baseline. Pay per deal returned, MCP-ready for Claude and other AI agents.
johnisanerd/claude-skill-google-flights-deals · ★ 0 · API & Backend · score 63

Install: claude install-skill johnisanerd/claude-skill-google-flights-deals

# Google Flights Deals, With Real Bargains Separated From Cheap Short-Hauls One airport code in, thirty destinations out, each flagged for whether it actually beats what that route normally costs. ## When to use this skill - The user wants "flight deals" or "cheap flights from" a specific airport. - They know where they are leaving from but not where they are going. - They want fare-drop discovery for a newsletter, affiliate site, or travel agent. - They need the cheapest destinations filtered to nonstop, business class, or a weekend-length trip. Not for: pricing a route you have already chosen (use `johnvc/Google-Flights-Data-Scraper-Flight-and-Price-Search` and the apify-google-flights-api skill) or building a fare history over time (use the companion apify-google-flights-tracking skill). See `references/actor-index.md`. ## Why the baseline matters Sort any deals feed by price and the top is dominated by short-haul routes that are cheap because they are close. Every row here also carries `average_price`, what that specific route typically costs, so `is_below_typical` tells you which fares are genuinely unusual. Measured across three hubs during the build, between 6 and 30 percent of a feed clears its own baseline on a given day. ## What you get One dataset row per destination. `result_type` separates `deal` rows from `error` rows: - `price`, `average_price`, `savings`, `savings_percent` - `is_below_typical`, true only when the fare beats that route's own norm - `na