A local-first skill for extracting structured mobility data from ride-sharing receipts to generate privacy-focused behavioral insights.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install nansui
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 nansui 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 Ride Insights?
Ride Insights is a privacy-first mobility intelligence skill designed to process ride-sharing receipts directly from your Gmail account. By leveraging Openclaw Skills, this tool ensures that sensitive financial and location data from providers like Uber, Bolt, and Lyft never leaves your local environment. It uses a loopback gateway to transform raw receipt HTML into structured data, allowing for deep analysis without compromising user privacy.
This skill is perfect for developers and data enthusiasts who want to audit their mobility spending, visualize travel patterns, or participate in DataHive missions. By running entirely on your local machine, it exemplifies the power of local-only agent processing for managing highly personal datasets.
Ride Insights Use Cases
- Building a private local database of ride history for long-term financial auditing.
- Identifying time-of-day travel patterns and recurring commute-like routes.
- Auditing mobility expenses across multiple platforms including Uber, Bolt, and Lyft.
- Generating anonymized datasets to participate in DataHive reward missions without exposing personal identifiers.
- Analyzing premium ride choices versus standard travel habits to optimize personal spending.
How Ride Insights Works
- The system initializes a local SQLite database using a predefined schema to store structured ride data.
- The gog CLI tool authenticates with Gmail to fetch ride-sharing receipt emails within a user-specified date range.
- Raw receipt HTML and JSON data are sent to a local OpenClaw Gateway loopback model for structured data extraction.
- Extracted trip details, such as cost, distance, and timestamps, are normalized and stored in the SQLite database.
- An AI agent analyzes the database to produce 8-10 behavioral insights regarding spending habits and location patterns.
- On request, the skill generates an anonymized CSV report where timestamps are rounded to 15-minute intervals and personal addresses are removed.
Ride Insights Setup
Ensure you have the gog CLI and python3 installed. Your environment must have a local OpenClaw Gateway running.
Configure your environment variables:
export OPENCLAW_GATEWAY_TOKEN="your_token"
export OPENCLAW_GATEWAY_URL="http://localhost:8000"
export OPENCLAW_GATEWAY_MODEL="your_model"
Initialize the local database:
python3 skills/ride-insights/scripts/init_db.py \
--db ./data/ride-insights/rides.sqlite \
--schema skills/ride-insights/references/schema_rides.sql
Fetch your emails (replace with your Gmail account):
python3 skills/ride-insights/scripts/fetch_emails_json.py \
--account [email protected] \
--out ./data/ride-insights/emails.json
Ride Insights Data Schema & Taxonomy
The skill organizes data into several local artifacts to ensure privacy and queryability:
| Artifact | Format | Description |
|---|---|---|
| emails.json | JSON | Stores raw fetched receipt content, including HTML payloads. |
| rides.json | JSON | Contains structured ride records extracted by the gateway model. |
| rides.sqlite | SQLite | A relational database for performant querying and insight generation. |
| anonymized_rides.csv | CSV | A shareable, privacy-safe export with obfuscated timestamps and locations. |
Ride Insights Advanced Features
- Local-only enforcement: The skill strictly refuses any non-local Gateway host to protect sensitive financial data.
- Smart Checkpointing: Automatically skips emails that have already been processed during extraction to save tokens and time.
- Multi-Provider Support: Integrated support for Uber, Bolt, Yandex, Lyft, Free Now, Curb, and Via.
- DataHive Integration: Built-in exporter for generating DataHive-ready reports for mobility missions.
- Token Management: Default processing caps and user-approval workflows for large receipt batches to control costs.
SKILL.md
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