A comprehensive Python-based skill for AI agents to retrieve and analyze mobile application performance data via the UMeng API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install umeng-api
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 umeng-api 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 UMeng API Analytics Skill?
The UMeng API skill provides a powerful Python SDK wrapper for the UMeng Open API, enabling AI agents to programmatically access critical application metrics. By leveraging Openclaw Skills, developers can automate the retrieval of user growth data, engagement levels, and anomaly detection reports without manual intervention. This skill acts as a bridge between the UMeng gateway and your coding agent, facilitating deep data analysis and reporting.
Built on a robust AOP SDK, it supports a wide variety of metrics including active users, new installations, and retention rates. It is designed with security in mind, offering multiple authentication methods and supporting local configuration files to keep sensitive API credentials safe while providing high-speed access to the UMeng UApp data suite.
UMeng API Analytics Skill Use Cases
- Monitoring daily active users and new user acquisition trends for specific mobile applications.
- Generating automated anomaly attribution reports to identify sudden spikes or drops in traffic.
- Tracking long-term retention rates and session durations across different application versions.
- Analyzing channel-specific performance to optimize digital marketing campaigns.
- Programmatic fetching of version-specific data for comparative product analysis.
How UMeng API Analytics Skill Works
- The AI agent initializes the skill and searches for authentication credentials in the umeng-config.json file or environment variables.
- The user provides a target AppKey and specifies the metrics or date range required for analysis.
- The skill utilizes the internal AOP SDK to construct a signed request to the UMeng API gateway (gateway.open.umeng.com).
- The UMeng server validates the credentials and processes the query for the requested statistical indicators.
- The skill receives the raw JSON response, parses the data into a readable format, and returns the results to the agent.
UMeng API Analytics Skill Setup
To use this skill within the Openclaw Skills ecosystem, you must first obtain your apiKey and apiSecurity from the UMeng developer platform.
Create a configuration file named umeng-config.json in your project root or home directory:
{
"apiKey": "your_api_key",
"apiSecurity": "your_api_security"
}
Alternatively, you can set the credentials as environment variables in your terminal:
export UMENG_API_KEY="your_api_key"
export UMENG_API_SECURITY="your_api_security"
No additional dependencies are required as the AOP SDK is pre-packaged within the skill structure.
UMeng API Analytics Skill Data Schema & Taxonomy
The skill organizes data based on UMeng's standard UApp taxonomy. Below is the primary structure used for queries:
| Attribute | Description | Format |
|---|---|---|
| AppKey | The unique identifier for the target application | String |
| startDate | The beginning of the tracking period | YYYY-MM-DD |
| endDate | The end of the tracking period | YYYY-MM-DD |
| periodType | The granularity of the data | daily, weekly, monthly |
Response objects typically include arrays such as newUserInfo or activeUserInfo, which contain value-date pairs for the requested metrics.
UMeng API Analytics Skill Advanced Features
- Multi-level configuration discovery (checks current directory, home folder, and skill directory).
- Support for advanced UApp metrics including
UmengUappGetRetentionsRequestandUmengUappGetChannelDataRequest. - Integrated outlier detection logic for automated performance monitoring and anomaly alerts.
- Secure credential management using external JSON files to prevent hardcoding sensitive keys.
- Native compatibility with Openclaw Skills for multi-agent data synthesis and cross-platform reporting.
SKILL.md
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