A smart flight comparison tool that automatically finds the most cost-effective and time-efficient multi-city travel routes from natural language input.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install multi-city-flight-optimizer
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 multi-city-flight-optimizer 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 Multi-City Flight Optimizer?
The Multi-City Flight Optimizer is a specialized AI agent skill designed for users who plan complex, multi-destination international trips. Instead of manually searching for every possible leg of a journey, this skill interprets natural language constraints to search for flight matrices across multiple candidate cities. It is a powerful addition to the library of Openclaw Skills that bridges the gap between raw flight data and actionable travel itineraries.
By intelligently combining outbound and return flights, the optimizer calculates a multi-dimensional score for every possible combination. This allows the AI to provide a comprehensive solution for cross-border travelers, ensuring they get the best balance of price, convenience, and travel time without the pain of manual拼接.
Multi-City Flight Optimizer Use Cases
- Planning complex holiday trips across several European or Asian cities to find the best entry and exit points.
- Finding the cheapest intercontinental flight combinations for long-haul journeys with flexible destinations.
- Optimizing business travel routes to cover multiple client locations within a specific holiday or work window.
- Comparing open-jaw flight tickets where you arrive in one city and depart from another to avoid backtracking.
How Multi-City Flight Optimizer Works
- The AI identifies user intent and extracts constraints like origin city, candidate destinations, and holiday time windows from natural language.
- It queries the local memory system to check for saved user preferences such as preferred departure airports or maximum transfer limits.
- The skill initiates a parallel full scan using the FlyAI toolset to search for all possible flight legs to and from every candidate city.
- A scoring model calculates a composite score for each combination based on price, transfer count, and total flight duration.
- The system filters out unreasonable combinations (e.g., excessive layovers) and outputs the Top 3 plans along with a generated HTML visualization file.
Multi-City Flight Optimizer Setup
To use this skill within your AI agent environment, ensure the FlyAI CLI tools are accessible. Since the skill uses specialized search commands, you must handle SSL requirements for the underlying API calls.
# The skill utilizes the FlyAI search-flight command internally
# Ensure environment variables are set to allow secure API communication
export NODE_TLS_REJECT_UNAUTHORIZED=0
No further manual installation is required once the SKILL.md is registered in your Openclaw Skills directory.
Multi-City Flight Optimizer Data Schema & Taxonomy
The skill organizes flight constraints and results using a structured schema to ensure accuracy across Openclaw Skills workflows:
| Field | Type | Description |
|---|---|---|
origin |
String | The primary departure city (e.g., Hangzhou). |
candidates |
Array | List of potential destination cities to compare. |
date_range |
Object | Includes start and end windows for departure and return. |
priority |
String | Scoring weight preference (Cheapest, Fastest, or Optimal). |
output_file |
Path | The generated HTML comparison report for the user. |
Multi-City Flight Optimizer Advanced Features
- Smart Memory Integration: Remembers your frequent departure cities and travel preferences to skip repetitive questions in future sessions.
- Ground Transport Logic: Suggests high-speed rail or bus connections between cities to create a seamless loop itinerary.
- Parallel Multi-City Search: Executes multiple flight queries simultaneously to significantly reduce wait times within Openclaw Skills.
- Automated Visualization: Generates a standalone HTML comparison page that can be shared with travel companions or saved as a PDF report.
SKILL.md
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