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The author built a grocery skill for a local Qwen 3.6 27B model that knows their fridge contents, past orders and real-time stock, and it ordered products for them online.
The author built a grocery skill for a local Qwen 3.6 27B model that knows their fridge contents, past orders and real-time stock, and it ordered products for them online.
The author built a grocery shopping skill for a local Qwen 3.6 27B model. It gives the model a loose picture of what's in their fridge, about 10 representative past orders covering preferences and local shops and SKUs, and real-time in-stock information. With that in context, the model placed an online grocery order.
The order went through while the author was cooking pasta, and they say the local model fully solved the real-time stock problem that cooking-ingredient delivery products never did. Open-ended or ambitious tasks still go faster with Claude or ChatGPT.
It works best when the answer is already in the context, so the effort goes into building a knowledge base: fridge contents, order history, and live stock data.
Build me a grocery skill that reads my fridge list in [file or note], my past orders from [store], and current stock at [store website]. Then fill a cart with what I'm running low on for [number] days of meals. Pause and show me the cart and total before checkout, and stop once I've approved the order.
Chrome auto browse with Gemini searched Etsy, added items to the cart, applied discount codes and left the cart ready for the user to review.
An agent runs overnight, collects the author's AI newsletter subscriptions and produces a daily podcast to listen to on walks.
Commenters use agents for weekly meal planning, daily briefs, errand tracking, email sorting, home repair load and household task organization.