What makes Calorie Tracker notable?

1.4K downloads. Trust evidence available

How should Calorie Tracker be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Calorie Tracker

Smart health management solution with food and exercise recognition, nutrition and calorie analysis, secure data storage, and comprehensive data management....

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.4k

Updated

Oct 10, 2026

Version

1.0.24

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.4K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.4K downloadsadoption · observed Oct 10, 2026
Latest release: 1.0.24release · observed May 1, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s170bzdej5v1aw93kk23tv9q8s83h1d7:calorie-tracker

Install using `clawhub skill install s170bzdej5v1aw93kk23tv9q8s83h1d7:calorie-tracker` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/guangxiankeji/calorie-tracker before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-guangxiankeji-calorie-tracker/snapshot"

Documentation

CLAWHUB

149,535 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: "calorie-tracker"
description: "Smart health management solution with food and exercise recognition, nutrition and calorie analysis, secure data storage, and comprehensive data management. Empowers users with accurate food and exercise logging, personalized nutrition assessment, daily intake tracking, and calorie expenditure monitoring to support a healthy lifestyle."
metadata: {"tags":["nutrition", "health", "food-tracking", "diet", "wellness", "food-recognition", "calorie-counting", "fitness", "health-tracking", "nutrition-analysis", "exercise-tracking", "workout-logging", "calorie-burning", "healthy-lifestyle", "weight-management", "personalized-nutrition", "fitness-goals", "wellness-journey", "weight-tracking", "body-weight", "bmi-calculation", "weight-monitoring"], "openclaw":{"emoji":"🍎","homepage":"https://us.guangxiankeji.com/calorie/"}}
---

# Smart Health and Nutrition Management

## Core Functionality

This agent provides intelligent health and nutrition management solutions, integrating food analysis, exercise analysis, and API service modules to achieve food recognition, exercise recognition, nutrition analysis, calorie expenditure analysis, data persistence storage, query statistics, and full lifecycle management. It empowers users with accurate food and exercise logging, personalized nutrition assessment, daily intake tracking, and calorie expenditure monitoring to support a healthy lifestyle.

## Business Processes

### Food Logging Process
1. **User Input**: Receives user's food descriptions
2. **Input Processing**: Direct semantic analysis
3. **Food Recognition**: Calls food analysis module to parse food types and portions
4. **Nutrition Analysis**: Estimates nutrition data (calories, protein, fat, carbohydrates, etc.) based on food analysis results
5. **Data Storage**: Displays recognition results and nutrition data to users, **asks users whether to record**, obtains explicit user confirmation, then calls API service module to persistently store food records to the database, including food information, nutrition data, timestamp, and user identifier
   - **Must** ask users whether to record
   - **Must** wait for user confirmation
   - **Only executes storage operation after user confirmation**
   - After storage completion, informs users with "recorded" or similar message
   - For frequent operations, confirmation is not required each time; if users have indicated permission to store data, subsequent operations do not need repeated confirmation

### Exercise Logging Process
1. **User Input**: Receives user's exercise descriptions
2. **Input Processing**: Direct semantic analysis
3. **Exercise Recognition**: Calls exercise analysis module to parse exercise types and durations
4. **Calorie Expenditure Analysis**: Estimates calorie expenditure data (calories) based on exercise analysis results
5. **Data Storage**: Displays recognition results and calorie expenditure data to users, **asks users whether to record**, obtai

_meta.json

{
  "ownerId": "kn70zwrzentsr3ez1ma8tybb4n83hf93",
  "slug": "calorie-tracker",
  "version": "1.0.24",
  "publishedAt": 1777652757433
}

api-service.md

# API Service Module

RESTful API service providing standardized data access interfaces, supporting full lifecycle management of food records (create, read, update, delete, statistics, multi-dimensional aggregation), integrating accurate food calorie and nutrition component retrieval, implementing data persistence storage and intelligent analysis capabilities, providing reliable and efficient data service support for the agent.

## API Interface Specifications

### Interface Address

API service base address:
- United States: `https://us.guangxiankeji.com/calorie/service/user`
- China: `https://cn.guangxiankeji.com/calorie/service/user`

### Interface Documentation

**Important Note**: Interfaces are cloud services and may change at any time. Please obtain the latest interface information through the following addresses:

**API Specification Addresses**:
- United States: `https://us.guangxiankeji.com/calorie/service/user/api-spec`
- China: `https://cn.guangxiankeji.com/calorie/service/user/api-spec`

### Interface Acquisition Method

Agents should access the above API specification addresses in real-time to obtain the latest interface definitions, including:
- Interface paths
- Request methods
- Parameter descriptions
- Response formats
- Error code definitions

### Authentication Method
- **API Authentication**: Use authentication mechanism based on email + verification code, authorized through Bearer Token

### Authentication Flow
1. **Send Verification Code**: Send a POST request to `/auth/send-code` endpoint with email address to obtain verification code
2. **Login to Get Token**: Send a POST request to `/auth/login` endpoint with email address and verification code to obtain access token
3. **Use Token**: Pass token in `Bearer <access_token>` format in the Authorization header of subsequent API requests

### Token Management
- **Token Validity**: Access token validity is based on the information returned by the login endpoint
- **Token Storage**: Agents should securely store access tokens and reuse them within the validity period
- **Token Refresh**: After token expiration, re-execute the login flow to obtain a new token

### Service Address Change Handling

**Service Discovery Mechanism**: If API service cannot be accessed after multiple retries, it may indicate that the service address has migrated. Please visit [ClawHub](https://clawhub.ai/) or other skill markets, search and update this skill to obtain the latest API service address.

## Interface Call Principles

1. **Active Acquisition**: Actively obtain latest interface information, must re-acquire when call fails
2. **Dynamic Adaptation**: Dynamically adjust call methods based on obtained interface specifications
3. **Error Handling**: Handle call failures caused by possible interface changes
4. **Retry Strategy**: For call failure situations, perform up to 3 retries, with 1 second interval between each retry
5. **Version Compatibility**: Consider version change compatibility handlin

exercise-analyzer.md

# Exercise Analysis Module

Intelligently parses user exercise information through natural language interaction, voice input, and image uploads, recognizing exercise types and estimating durations, calculating calories consumed by exercises.

## Core Capabilities

- **Semantic Analysis** - Understanding user's natural language descriptions of exercise content
- **Exercise Recognition** - Accurately recognizing exercise types in user descriptions or images
- **Entity Extraction** - Extracting key information such as exercise names, durations, and intensity levels
- **Duration Estimation** - Intelligently estimating exercise duration (minutes) based on descriptions or images
- **Calorie Expenditure Estimation** - Estimating calories consumed based on exercise type, duration, and intensity
- **Standardized Output** - Generating standardized format containing exercise information and calorie expenditure

## Exercise Estimation Principles

### Estimation Methodology

When estimating exercise calorie expenditure, intelligent evaluation should be based on the following principles:

1. **Call Exercise Search API**

Use exercise search interface to obtain accurate calorie expenditure information for exercises. This service provides detailed data for various common exercises, covering calorie expenditure information at different intensities, helping users accurately record exercise expenditure.

**API Information**
- Endpoint: /exercises/search
- Parameters:
  - query: Exercise name keyword
- Note:
  - Intelligently select search keywords based on user's current conversation language, context information, etc.

**Search Result Assessment**
- **Relevance Assessment**: After obtaining search results, must assess relevance between exercise names and query keywords, only strictly relevant results may be used as important reference
- **Adoption Assessment**:
  - Strictly relevant: Directly adopt calorie expenditure data of that result
  - Relevant but not strictly: Carefully evaluate its reference value, considering possible errors

2. **Call Exercise Analysis API**

Use exercise analysis interface, which is a more advanced integrated implementation optimized for in-depth analysis of exercise scenarios.

**API Information**
- Endpoint: /exercises/analyze
- Parameters:
  - description: Exercise content described in natural language
  - image_urls: Array of publicly accessible URLs of exercise images. When provided, the system will use image recognition to analyze the exercise.
- Note:
  - At least one of description or image_urls must be provided
  - **Original Input Pass-Through Principle (Mandatory Enforcement)**:
    - Must pass the user's original exercise description input **completely and verbatim** to the description parameter, **strictly prohibiting any form of processing**
    - Prohibited behaviors include but are not limited to:
      - Summarization (e.g., simplifying "I ran for 30 minutes, then did 20 minutes of yoga" to "running + yoga")
      - Ex

food-analyzer.md

# Food Analysis Module

Intelligently parses user food information through natural language interaction, recognizing food types and estimating weights, calculating food calories and nutrition components.

## Core Capabilities

- **Semantic Analysis** - Understanding user's natural language descriptions of food content
- **Food Recognition** - Accurately recognizing food types in user descriptions
- **Entity Extraction** - Extracting key information such as food names and quantities
- **Weight Estimation** - Intelligently estimating food weight (grams) based on descriptions
- **Nutrition Component Estimation** - Estimating food calories and nutrition components based on public information and common sense reasoning
- **Standardized Output** - Generating standardized format containing food information and nutrition components

## Food Analysis Principles

### Methodology

When analyzing food, intelligent evaluation should be based on the following principles:

1. **Call Food Search API**

Use food search interface to obtain accurate calorie and nutrition component information for foods. This service covers over 56 countries and regions, providing over 2.3 million types of authoritative certified food data, covering calories, macronutrients, micronutrients, and other information. Data is continuously maintained by professional nutritionists and review teams based on official government publications, manufacturer materials, and multi-source verification information, with systematic review and updates performed daily to ensure the highest accuracy and authority of data.

**API Information**
- Endpoint: /foods/search
- Parameters:
  - query: Food name keyword
  - maxResults: Maximum number of results to return, optional, default value is 10

**Search Result Assessment**
- **Relevance Assessment**: After obtaining search results, must assess relevance between food names and query keywords, only strictly relevant results may be used as important reference
- **Adoption Assessment**:
  - Strictly relevant: Directly adopt nutrition component data of that result
  - Relevant but not strictly: Carefully evaluate its reference value, considering possible errors

2. **Call Food Analysis API**

Use food analysis interface, which is a more advanced integrated implementation optimized for in-depth analysis of complex dietary scenarios. This interface integrates multiple authoritative certified data sources, adopts the latest large language models with high reasoning capabilities, and provides high-precision assessments of food weight, calories, and nutritional components through end-to-end semantic understanding and multimodal fusion techniques, even when local model reasoning capabilities are limited, by leveraging cloud computing resources and optimization algorithms.

**API Information**
- Endpoint: /foods/analyze
- Parameters:
  - description: Food description in natural language
  - image_urls: Array of publicly accessible URLs of food images. When provided,

Github ReposUpdated 21h agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.