An AI-driven food nutrition calculator that uses vision recognition to identify meals and calculate caloric data automatically.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install calorie1
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 calorie1 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 Calorie Detective?
Calorie Detective is a powerful AI agent skill designed to simplify diet management through advanced visual recognition. By utilizing the Kimi Vision API, it acts as a digital nutritionist that can identify food items from photos and provide a comprehensive breakdown of calories, proteins, carbohydrates, and fats. It is specifically optimized for Chinese cuisine, making it highly effective at identifying complex dishes that standard applications often struggle with.
As part of the Openclaw Skills ecosystem, Calorie Detective helps users uncover hidden calories in their meals with the precision of a detective. The tool includes a built-in database of over 100 common foods and provides actionable health advice based on the identified nutritional content, supporting users in their weight loss, fitness, or general health journeys.
Calorie Detective Use Cases
- Automatically tracking daily caloric intake by simply taking photos of meals
- Analyzing the macronutrient content of complex home-cooked or restaurant dishes
- Generating detailed nutritional reports for fitness and diet progress monitoring
- Receiving personalized health suggestions based on dietary patterns
- Customizing a personal food database for niche or specific regional ingredients
How Calorie Detective Works
- The user provides a photo of their food to the AI agent.
- The Kimi Vision API (moonshot-v1-8k-vision-preview) processes the image to identify the food items present.
- The skill matches the identified food against an internal database or uses the LLM's knowledge for nutritional estimation.
- Calorie Detective calculates the total calories and macronutrients (protein, fat, carbs) for the portion.
- The system generates a formatted nutrition report including health improvement tips for the user.
Calorie Detective Setup
To get started with this tool in your Openclaw Skills environment, follow these steps:
# Ensure your environment has access to the Kimi/Moonshot Vision API
# Navigate to the skill directory
cd calorie-detective-v2-0-0
# Configure your API credentials in your environment variables
export MOONSHOT_API_KEY='your_api_key_here'
You can extend the built-in database by modifying the COMMON_FOODS dictionary in src/calorie_calculator.py to include your own specific food items and their nutritional values.
Calorie Detective Data Schema & Taxonomy
The skill organizes food data in a structured format within the application logic. The primary data schema for food items includes:
| Field | Description |
|---|---|
| calories | Energy value per 100g |
| protein | Protein content in grams per 100g |
| carbs | Carbohydrate content in grams per 100g |
| fat | Fat content in grams per 100g |
All reports generated by the skill are formatted in Markdown for easy reading and integration into other health tracking Openclaw Skills workflows.
Calorie Detective Advanced Features
- Advanced computer vision support via moonshot-v1-8k-vision-preview
- Specialized recognition engine optimized for diverse Chinese culinary styles
- Built-in local database featuring 100+ common food types for offline reference
- Automated health advice generation based on meal analysis results
- Extensible Python-based dictionary for developers to add custom food nutritional data
SKILL.md
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