A specialized analytical tool for extracting and grouping Juss Sports App order metrics across flexible time granularities like hours, days, or months.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install app-order-date-key-stats
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 app-order-date-key-stats 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 Juss Sports App Order Statistics Skill?
This skill enables AI agents to perform sophisticated data analysis on Juss Sports App order records. By leveraging a structured SQL template with dynamic grouping capabilities, it allows developers and analysts to track key performance indicators (KPIs) such as unique user counts, total order volume, and net sales revenue. It is designed to work seamlessly within Openclaw Skills environments, providing a secure, read-only interface to the underlying data warehouse.
The primary value lies in its flexibility and safety. Users can filter by specific keywords in order titles or descriptions while choosing the temporal granularity that fits their needs—whether it's monitoring hourly peaks or monthly trends. The built-in guardrails ensure that only authorized analytical queries are executed, maintaining the integrity of the database.
Juss Sports App Order Statistics Skill Use Cases
- Analyzing order volume and revenue trends during specific sports events or promotion periods.
- Monitoring hourly payment success and refund rates to identify potential system issues or peak traffic.
- Searching for specific order types using keywords to calculate niche market performance.
- Generating monthly financial summaries for net sales and user growth within Openclaw Skills.
How Juss Sports App Order Statistics Skill Works
- The user provides query parameters including a start date, end date, optional search keywords, and a time dimension (hour, day, or month).
- The skill validates the parameters and requests confirmation from the user to ensure accuracy.
- A dynamic SQL query is constructed by injecting the chosen time dimensions and keyword filters into a secure, pre-defined template.
- The Python execution environment connects to the Juss Sports data warehouse using read-only credentials.
- Results are processed using Pandas and formatted into a clean Markdown table for the user, accompanied by a natural language summary of the findings within the Openclaw Skills framework.
Juss Sports App Order Statistics Skill Setup
Ensure you have Python installed and the required environment variables configured for database access.
# Install dependencies
pip install mysql-connector-python pandas tabulate
# Set environment variables
export JIUSHI_DB_HOST='your_host'
export JIUSHI_DB_USER='juss_dw_ro'
export JIUSHI_DB_PASSWORD='your_password'
export JIUSHI_DB_NAME='juss_dw'
Add the skill configuration to your directory to enable the agent to recognize the app-order-date-key-stats command.
Juss Sports App Order Statistics Skill Data Schema & Taxonomy
The skill queries the juss_dw.app_j_order table and produces a report with the following structure:
| Field | Description | Type |
|---|---|---|
| order_date | The date (or hour/month) of the transaction | Date/String |
| 用户数 | Count of unique user IDs | Integer |
| 订单数量 | Total count of orders in the period | Integer |
| 未支付订单数 | Orders with state 'ORDER_CLOSED' | Integer |
| 退款订单数 | Orders with refund-related states | Integer |
| pay_amount | Total amount paid (converted from cents to units) | Decimal |
| refunded_amount | Total amount refunded | Decimal |
| sales_amount | Net sales (pay_amount - refunded_amount) | Decimal |
Juss Sports App Order Statistics Skill Advanced Features
- Dynamic SQL Grouping: Automatically adjusts the GROUP BY clause based on user-requested granularity (Hour, Day, Month).
- Keyword-Based Filtering: Supports multi-keyword search within order titles and descriptions using flexible LIKE conditions.
- Security Guardrails: Enforces a strict read-only policy with a dedicated user and blocks any non-SELECT SQL commands to maintain safety within Openclaw Skills.
- Environment Variable Integration: Securely handles database credentials via system environment variables for production-ready deployments.
SKILL.md
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