An AI-powered nutrition analysis tool equipped with a 2,000+ entry Chinese food database, designed to parse natural language meal descriptions and track goal-oriented macro targets.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install nutri-calc
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install nutri-calc using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Nutri Calc?
Nutri Calc is a highly specialized health intelligence tool that brings precision nutrition tracking to conversational AI. Leveraging an expansive database of over 2,000 Chinese food entries, this tool allows users to input natural language food descriptions and automatically parses complex meal compositions, regional dish variations, and common Chinese serving units. As a key addition to your collection of Openclaw Skills, it bridges the gap between raw culinary inputs and deep physiological data analysis.
By integrating established metabolic formulas such as the Mifflin-St Jeor equation, the tool calculates Basal Metabolic Rate (BMR) and Total Daily Energy Expenditure (TDEE). Whether your goal is muscle gain, fat loss, or weight maintenance, it offers color-coded comparisons, targeted gap analysis, and culturally relevant dietary adjustments to ensure you hit your precise macronutrient targets with minimal friction.
Nutri Calc Use Cases
- Natural Language Meal Logging: Quickly log Chinese dishes using standard conversational phrases like "早餐两个鸡蛋+牛奶" without manual database lookups.
- Precision Fitness Goal Tracking: Compute and monitor caloric and macro targets adjusted dynamically for weight loss, maintenance, or muscle building.
- Dietary Gap Remediation: Identify daily protein, fat, or carbohydrate deficiencies and receive tailored, culturally appropriate food recommendations to correct them.
- Multi-Day Progress Auditing: Track continuous metabolic data over time, mapping weekly averages and caloric trends to prevent drastic nutritional swings.
How Nutri Calc Works
- Natural Language Processing: The system parses free-text meal entries and segments them into individual food items, accurately converting informal Chinese portion sizes (e.g., 碗, 份, 两, 个) into precise gram equivalents.
- Database Querying: It matches segmented food items against a database containing over 2,000 native Chinese food listings, retrieving macronutrients, fiber, and sodium metrics per serving.
- Metabolic Baseline Calculations: User profile parameters (height, weight, age, activity levels) are fed into the Mifflin-St Jeor formula to determine active daily calorie and macro splits.
- Real-Time Discrepancy Analysis: The engine compares actual intake against target requirements, rendering visual color-coded warnings for off-target elements.
- Optimization & Reporting: It provides actionable dietary corrections and outputs structured markdown reports, complete with a five-dimensional radar chart and multi-day trend analysis.
Nutri Calc Setup
Installation
Install the nutri-calc module directly into your local CLI environment:
npm install -g @openclaw/nutri-calc
CLI Configuration
Initialize the tool and set up your initial physical profile:
nutri-calc init --weight 75 --height 178 --age 30 --gender male --activity moderate --goal muscle
Verification
Verify the system can resolve Chinese culinary terms correctly with a simple test:
nutri-calc analyze --food "一碗兰州牛肉面"
Nutri Calc Data Schema & Taxonomy
Nutritional Database & Profile Taxonomy
The nutri-calc module structures profile telemetry, meal logs, and metabolic targets using a clean relational model. Developers can query history and export tables using standard configurations.
| Data Category | Parameter / Field | Type | Description |
|---|---|---|---|
| User Profile | weight, height, age, gender, activity, goal |
Numeric / Enum | Baseline inputs to evaluate BMR and target macros (muscle, fat-loss, maintenance). |
| Database Items | calories, protein, fat, carbs, fiber, sodium |
Float / Integer | Standardized nutrients analyzed per 100g or serving. |
| Meal Log Metrics | meal_time, raw_text, parsed_items, servings |
Object / String | Structured output from NLP parser representing daily consumption. |
| Target Thresholds | actual_vs_target, variance_percentage |
Percentage / Color-code | Evaluates nutritional status (Green: <10%, Yellow: 10-20%, Red: >20%). |
Nutri Calc Advanced Features
- Intelligent Supplement Recommendations: Offers automated dietary alternatives based on active meal context, suggesting high-yield adjustments like adding 30g of soy milk or braised beef to close macro gaps.
- Multi-Day Trend Analytics: Compiles consecutive tracking sessions to construct robust mathematical models representing calorie deficits, surpluses, and weekly variance warnings.
- Interoperability with Openclaw Skills: Easily triggers structured markdown reports and data pipelines that integrate into other developer productivity tasks and automated workflows.
- Exportable Telemetry Reports: Compiles high-fidelity nutritional audit sheets complete with text-based 5-dimension radar charts ready for dashboard publishing.
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