A decisive AI dining companion that automates meal planning and restaurant discovery through smart logic and map integrations.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install eat-skill
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 eat-skill 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 Dining Decision Assistant (eat-skill)?
eat-skill is a specialized AI agent skill designed to solve the universal problem of mealtime indecision. Functioning as a digital dining buddy, it moves beyond simple search results by providing authoritative recommendations based on user preferences, budget, time, and even current weather conditions. By integrating this into Openclaw Skills, users gain access to a personality-driven assistant that manages a local database of preferences and dining history to ensure variety and satisfaction in every meal.
The skill adopts a practical and slightly witty persona, aiming to be a helpful friend rather than a generic food blogger. It prioritizes decisiveness and value-for-money, making it an essential tool for developers and power users who want to optimize their daily routines without the mental fatigue of choosing where to eat.
Dining Decision Assistant (eat-skill) Use Cases
- Automating daily lunch decisions based on office proximity and budget constraints.
- Discovering new restaurants using real-time AMAP LBS integration in unfamiliar locations.
- Managing group dining scenarios such as team building, dating, or business treats with specialized modes.
- Maintaining a structured dining history to prevent repetitive meal recommendations over a 3-day cycle.
- Generating custom restaurant skills from map data for quick reference in the future.
How Dining Decision Assistant (eat-skill) Works
- Initializes by checking for a user-profile.json file to understand your location, taste preferences, and budget.
- Analyzes contextual triggers including the time of day (breakfast vs. late-night snack) and current weather conditions.
- Filters potential options by excluding restaurants or categories visited within the last three days via the history log.
- Employs a randomized fun mechanism such as dice, wheels, or fate to select a food category if the user is undecided.
- Executes a multi-stage search starting with local restaurant skills, then falling back to the AMAP API for nearby POI data.
- Presents a final recommendation with specific dish suggestions, navigation routes, and budgeting tips.
Dining Decision Assistant (eat-skill) Setup
To get started with this skill in your environment, follow these steps:
# Install via OpenClaw
npx clawhub install eat-skill
# Manual installation for Claude Code
git clone https://github.com/funAgent/eat-skill.git ~/.claude/skills/eat-skill
# For Cursor users
git clone https://github.com/funAgent/eat-skill.git .cursor/skills/eat-skill
# Set up AMAP API Key for discovery and navigation
export AMAP_WEBSERVICE_KEY="your_api_key_here"
Dining Decision Assistant (eat-skill) Data Schema & Taxonomy
The skill organizes user data and restaurant information using a structured JSON format to ensure persistence across sessions in Openclaw Skills.
| Component | Format | Description |
|---|---|---|
| user-profile.json | JSON | Stores location, taste (likes/dislikes), budget, and diet info |
| history | Array | A list of dates, food types, and restaurants visited |
| restaurants/ | Directory | Contains individual Markdown or JSON files for specific restaurant skills |
| AMAP Integration | API | Connects to external LBS data for POI and route planning |
Dining Decision Assistant (eat-skill) Advanced Features
- Scenario-based modes including /eat-boss for high-end dining and /eat-broke for budget-friendly options.
- Automated POI-to-Skill generator that converts map search results into permanent restaurant database entries.
- Intelligent navigation planning with support for walking, driving, and public transit routes via AMAP.
- Competitive comparison mode using /eat-pk to help users choose between two specific dining venues.
- Sentiment-aware feedback loop via /eat-review to update the user profile based on meal satisfaction.
SKILL.md
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