feast_skill

Overview

This skill is a comprehensive meal planning system designed to turn weekly cooking into a cultural experience. It creates fully self-contained weekly plans that include authentic recipes, regional context, curated playlists, and intelligent shopping lists. The system supports onboarding, daily reveals, price-aware shopping optimization, and end-of-week reviews.

How this skill works

Feast uses a weekly cadence: research and draft, confirm, generate shopping lists, daily reveals, and a review at week end. Each week's file embeds everything for the week: recipes (converted to the user’s preferred units), thematic research, playlists, and shopping details. Notifications and reminders are scheduled via cron-like jobs and delivered to the user’s chosen channel, with optional push notification support.

When to use it

• Plan weekly meals or a themed menu for a special week.
• Generate an optimized shopping list with price checks and store recommendations.
• Get recipe ideas, step-by-step cooking help, or unit conversions.
• Review past meals, update history, and track favourites or failures.
• Onboard a new user and capture preferences, dietary needs, and equipment.

Best practices

• Onboard users first to capture location, household size, dietary constraints, and preferred units.
• Run planning on the scheduled planning day to leverage seasonality and event research.
• Keep weekly plans self-contained so the week file can be archived or shared intact.
• Use shopping list price checks for the top 3–5 expensive items to reduce grocery spend.
• Encourage users to rate meals so history and recommendations improve over time.

Example use cases

• Create a week of Northern Thai meals with region-specific recipes and a Chiang Mai playlist.
• Generate a compact shopping list that combines overlapping ingredients and flags seasonal items.
• Prepare a dinner reveal that includes cultural context, the authentic recipe, and a 1–2 hour playlist.
• Run an end-of-week review to move favourites into a saved list and log failures to avoid repeats.
• Adjust meal suggestions for a user on a low-calorie phase while preserving cultural authenticity.