A diagnostic utility to run a minimal validation matrix across all Aliyun Model Studio AI capabilities.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install aliyun-modelstudio-entry-test
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 aliyun-modelstudio-entry-test 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 Aliyun Model Studio Entry Test?
The Aliyun Model Studio Entry Test skill provides a standardized framework for testing the full suite of Aliyun Model Studio integrations. It covers everything from text-to-image and video generation to real-time speech processing and visual reasoning. By executing a minimal request for each sub-skill, developers using Openclaw Skills can quickly verify connectivity, authentication, and model availability across the DashScope ecosystem.
This utility is essential for maintaining the reliability of AI agents that rely on Alibaba Cloud's Model Studio. It ensures that every specific capability—ranging from text embeddings to live speech translation—is functioning correctly within the Openclaw Skills environment before deploying complex workflows.
Aliyun Model Studio Entry Test Use Cases
- Verifying API connectivity and authentication for Aliyun Model Studio.
- Smoke testing AI capabilities like Wan Video or Qwen Audio after a configuration change.
- Benchmarking success rates and latency across different multimodal models.
- Generating a status report for all AI-driven Openclaw Skills in a specific environment.
How Aliyun Model Studio Entry Test Works
- Access the target sub-skill directory and parse the corresponding documentation for parameters.
- Select a minimal input example and the recommended model for the specific AI capability.
- Execute the SDK call or script using the DashScope environment and your API credentials.
- Capture the response metadata including duration, status, and output summaries.
- Aggregate all results into a structured markdown report for review and audit within Openclaw Skills.
Aliyun Model Studio Entry Test Setup
First, set up a virtual environment and install the necessary dependencies for these Openclaw Skills:
python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope
Then, configure your credentials by setting the environment variable:
export DASHSCOPE_API_KEY='your_api_key_here'
Ensure you have access to the specific model studio skills you intend to test within your repository structure.
Aliyun Model Studio Entry Test Data Schema & Taxonomy
The skill generates a detailed test report and stores evidence in a structured format. Results are saved as a markdown table to track the health of Openclaw Skills.
| Field | Description |
|---|---|
| Capability | The specific AI domain (e.g., TTS, Rerank, Omni) |
| Sub-skill | The internal path to the specific Openclaw Skills module |
| Model | The specific model ID used during the test |
| Status | Pass/Fail indication based on the API response |
| Request Summary | Brief description of the input payload |
| Evidence Path | Location of the raw API response and artifacts |
Aliyun Model Studio Entry Test Advanced Features
- Automated model list refreshing using specialized crawl-and-skill utilities.
- Support for both real-time and non-real-time audio processing validation.
- Multi-capability matrix execution for comprehensive system health checks of Openclaw Skills.
- Detailed artifact logging including region, resource IDs, and time ranges for reproducibility.
- Integration with visual reasoning and omni multimodal model testing pipelines.
SKILL.md
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