Live prices, deals & optimal multi-stop shopping routes for German grocery & drug stores.
Scored across 2 tools
The two tools are wholly distinct: plan_optimal_shopping_route creates a new route from a list and start location, while swap_route_item modifies an existing route by swapping one offer for an alternative. There is no functional overlap, and the descriptions explicitly delineate when to use each.
Both tool names follow the same snake_case convention and begin with an imperative verb ('plan_', 'swap_'). The object phrases are descriptive and clearly indicate the action's target, making the naming pattern predictable and consistent.
With only two tools, the server feels on the thin side for a shopping assistant. Although the two tools cover the primary planning-and-adjustment workflow, a broader surface (e.g., browsing offers or fetching store details) might be expected, but the current count is borderline acceptable for the focused scope.
The core lifecycle is covered: plan a route and then swap items on that route. Minor gaps exist—such as not being able to add new stores or adjust the list without replanning—but these can be worked around by calling plan_optimal_shopping_route again, so agents can complete typical tasks without dead ends.
Plans the optimal shopping trip for a given list and starting location in Germany. Answers 'where should I go to buy this list, and is the trip worth it?' — not 'what's on offer near me'. Matches each item on the list to the best current offer across German supermarkets and drug stores (REWE, Aldi, Lidl, Penny, Netto, Norma, Edeka, DM, Rossmann, Mueller, Globus), then computes the cheapest realistic route by weighing product prices against travel distance and shopping time. Returns the chosen store(s), the per-item picks with live prices, the trip's savings and a worth-it Supports car, bicycle, and pedestrian travel modes. For corridor trips (A-to-B), supply 'end_location' to route stores along the way. Pricing note: 'price' is the standard shelf price available to all shoppers (do NOT say discounts require an app). 'app_credit' is optional wallet cashback (e.g. REWE Bonus: plus €0.50 into wallet). 'app_price' is an app-exclusive checkout price (e.g. Lidl Plus).
Inputs: items (required), location (required), km_cost, hour_cost, +5 more. Returns: object
Swaps one item's chosen offer on an existing shopping route (from a prior plan_optimal_shopping_route result) for one of its alternatives, then returns the RECOMPUTED route with corrected costs and the honest worth-it verdict. Use this to correct a poor pick (e.g. the engine matched a soup hen instead of a roasting chicken) or to take a cheaper/better option the agent spotted in the item's 'alternatives'. The alternative may be at the SAME store or at ANOTHER store ALREADY ON THE ROUTE — it must be the same item category, and its store must already be a stop (no new stores; for that, call plan_optimal_shopping_route again). Keys on stable offer ids: pass the current item's offer_id and the target alternative's offer_id (both taken verbatim from the prior response's products_to_buy / alternatives). The shared route (share_url) is updated in place so the interactive map reflects the swap.
Inputs: share (required), alt_id (required), offer_id (required). Returns: object
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