A conversational AI skill for querying and booking flights, trains, and hotels using natural language processing.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install anidyforest2
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 anidyforest2 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 Trip Assistant?
Trip Assistant is a sophisticated conversational agent designed to streamline travel logistics and planning. It allows users to query flight availability, train schedules, and hotel accommodations through intuitive natural language commands in both English and Chinese. As a specialized component for Openclaw Skills, this tool handles complex date parsing and multi-city itineraries, providing a seamless bridge between user intent and backend booking systems.
Trip Assistant Use Cases
- Searching for real-time flight availability and ticket pricing across multiple airlines.
- Querying high-speed rail and traditional train schedules for domestic travel.
- Finding local hotel accommodations and lodging options based on specific proximity or dates.
- Generating comprehensive travel plans and identifying the fastest transit routes for complex trips.
How Trip Assistant Works
- The user submits a natural language travel query to the agent powered by Openclaw Skills.
- The skill triggers a Python script that captures the full original message and relevant user metadata.
- The request is transmitted to a FastAPI backend server which parses the intent and fetches data from the production or test environment.
- The system processes complex parameters like multi-city stops and relative dates.
- A human-readable response is returned and displayed to the user to facilitate immediate booking actions.
Trip Assistant Setup
To integrate this tool into your Openclaw Skills environment, first ensure the FastAPI backend is operational:
uvicorn booking_assitant.fastapi_serve:app --host 0.0.0.0 --port 8763
Then, execute queries using the query script with the necessary environment variables:
python SKILL_DIR/scripts/query.py \
--query "<user query>" \
--user-id "${BOOKING_API_USER_ID}" \
--env "prod" \
--base-url "http://host.docker.internal:8763"
Trip Assistant Data Schema & Taxonomy
The skill organizes its operations through a structured set of CLI parameters and environment configurations to ensure data integrity across Openclaw Skills workflows.
| Parameter | Description | Environment Variable |
|---|---|---|
| User ID | Unique identifier for tracking sessions | BOOKING_API_USER_ID |
| Environment | Target backend (prod or fat) | BOOKING_API_ENV |
| Base URL | Endpoint for the API server | BOOKING_API_BASE_URL |
| Query | The raw natural language input | N/A |
Trip Assistant Advanced Features
- Native support for complex Chinese travel queries including G-series high-speed rail.
- Intelligent date parsing for relative time references such as "next weekend" or "tomorrow afternoon".
- Multi-environment switching between production (prod) and test (fat) datasets for safe experimentation.
- Robust error handling for server connectivity and timeouts within the Openclaw Skills ecosystem.
SKILL.md
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