An automated QA skill that parses requirement documents to generate multi-dimensional test cases and exportable XMind mind maps.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install req-to-testcase
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install req-to-testcase using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
This skill provides a robust bridge between product requirements and quality assurance execution. By leveraging Openclaw Skills, developers and QA engineers can eliminate the manual drudgery of drafting test scenarios. The tool automatically parses various document formats, decomposes them into structured functional points, and applies five core testing dimensions—Positive, Negative, Boundary, Business Logic, and User Experience—to ensure maximum coverage.
Beyond simple text generation, it integrates directly with visualization tools by exporting results into native .xmind files. This ensures that the generated test logic is not only technically sound but also ready for stakeholder presentations and team brainstorming sessions, significantly accelerating the software development lifecycle.
Ensure the necessary Python environment is available and install the required dependencies for document parsing and XMind generation:
# Install document processing dependencies
pip install python-docx pypdf pandas xmind --break-system-packages
# Verify the script location
ls scripts/read_requirement_file.py
ls scripts/xmind_tools2.py
The skill organizes data into structured tables and hierarchical mind maps. Key data fields include:
| Field | Description |
|---|---|
| Case ID | Unique identifier (e.g., TP-001) |
| Module | The functional area associated with the requirement |
| Test Type | Classification (Positive, Negative, Boundary, etc.) |
| Priority | Ranked from P0 (Smoke) to P3 (UX/UI) |
| Steps | Numbered, actionable execution instructions |
| Expected Result | Clearly verifiable system behavior |
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