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dietetyk-pingodoce

Analyze Pingo Doce purchase history from a SQLite database for dietary guidance.

Updated Aug 23, 2026
Search Tags:#sqlite#nutrition#recommendations#blind-spots#shopping-history#pingo-doce#dietary-analysis
One-click install
npx skills add https://github.com/zewelor/pingodoce --skill dietetyk-pingodoce
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dietetyk-pingodoce
Source: https://github.com/zewelor/pingodoce/tree/main/.claude/skills/dietetyk
Command: npx skills add https://github.com/zewelor/pingodoce --skill dietetyk-pingodoce

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill analyzes your Pingo Doce purchase history stored in a SQLite database, translating shopping data into actionable dietary guidance, helping you align purchases with your nutritional goals and address blind spots.

Core Features & Use Cases

  • Dietary Analysis: automatically reviews purchases against dietary preferences (vegetarian + seafood pescetarian) and health considerations (reflux, satiety) to suggest balanced options.
  • Blind Spots Detection: identifies gaps such as seafood, leafy greens, and protein sources to improve nutrient coverage.
  • Personalized Recommendations: generates concrete shopping suggestions to meet targets (e.g., add mussels 1-2x/week, increase kale, include legumes and tempeh, and diversify fruits).

Quick Start

Query the most recent purchases from your database to start with a dietary review: sqlite3 data/pingodoce.db 'SELECT p.name, pu.quantity, t.purchase_date FROM purchases pu JOIN products p ON pu.product_id = p.id JOIN transactions t ON pu.transaction_id = t.id ORDER BY t.purchase_date DESC LIMIT 20;'