Body Shape Manager

The problem

Meal tracking often stalls on incomplete entries, rough calorie estimates, and delayed feedback. Looking up macros manually is slow, food names are inconsistent, and users may not know whether their protein target is met or their calorie deficit is too aggressive. body-shape-manager treats this as a conversational personal body-management workflow, combining meal capture, nutrition estimation, and goal-based feedback in one flow.

How it works

• First-run setup: If no profile exists, the skill collects basic information through six questions, validates answers with init_profile.py, and calculates daily nutritional targets using nutrition_calculator.py.
• Meal recording: It accepts plain-text entries such as rice 200g, egg 60g, splits items by commas, slashes, or natural language separators, fuzzy-matches common foods, and estimates nutrition for unknown items from general knowledge.
• Summaries and advice: It reads the daily log in memory/YYYY-MM-DD.md, summarizes calories and macros, and flags issues such as excessive deficit, high carbs, high fat, or low protein based on cut or bulk goals.
• Local storage: Core state is kept in references/user_profile.json and daily Markdown logs, without relying on an external database.

Boundaries and cautions

It is suited to text-first meal logging and lightweight body-shape tracking, not precise medical nutrition advice or complex exercise programming. Nutrition estimation depends on assumed food knowledge, so portion size, cooking method, and branded products can materially affect results; users should keep the original entry and verify important values.