Casely is an intelligent QA assistant for Openclaw Skills that transforms fragmented project documentation into structured, style-consistent test suites.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install casely
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 casely 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 Casely: AI-Powered QA Test Case Generator?
Casely is a professional-grade tool designed for Openclaw Skills to solve the manual bottleneck of test case creation. By analyzing requirement documents in various formats like PDF, DOCX, and XLSX, it automatically generates structured test suites that mirror your team's specific writing style and technical standards.
Built to integrate seamlessly into a developer or QA workflow, Casely uses advanced parsing to bridge the gap between messy documentation and clean, import-ready test data. It ensures that 100% of your team's naming conventions and column structures are preserved, making it an essential component for teams utilizing Openclaw Skills to accelerate their software development lifecycle.
Casely: AI-Powered QA Test Case Generator Use Cases
- Automating the extraction of test scenarios from complex requirement documents.
- Standardizing test case writing style across large, distributed QA teams.
- Converting legacy documentation into clean Markdown and structured Excel formats for TMS import.
- Rapidly generating negative, boundary, and integration test cases for new feature modules.
- Reducing the time spent on manual test planning and traceability mapping.
How Casely: AI-Powered QA Test Case Generator Works
- Initialize a new workspace and verify the environment dependencies using the /init command.
- Convert raw documents into structured Markdown using the built-in Docling parser via /parse.
- Analyze your team's existing examples to create a persistent style guide with the /style command.
- Scans requirements to suggest a comprehensive testing plan and risk-based coverage tiers using /plan.
- Generate atomic, one-scenario-per-file test cases that adhere to the style guide via /generate.
- Convert the finalized Markdown cases into formatted .xlsx files ready for Test Management System import using /export.
Casely: AI-Powered QA Test Case Generator Setup
To get started with Casely for Openclaw Skills, ensure you have the uv package manager installed. Follow these steps:
# Initialize the project environment
uv init
# Add required dependencies for document parsing and Excel export
uv add docling openpyxl
# Create your project structure
/init [ProjectName]
After setup, place your requirements in projects/[Name]/input/requirements/ and style examples in projects/[Name]/input/examples/.
Casely: AI-Powered QA Test Case Generator Data Schema & Taxonomy
Casely organizes data into a clear hierarchy to ensure traceability and ease of use within Openclaw Skills:
| Directory | Description |
|---|---|
input/requirements/ |
Raw requirement documents (PDF, DOCX, XLSX). |
input/examples/ |
Sample test cases used to learn your team's style. |
processed/ |
Markdown versions of all input documents. |
results/ |
Generated atomic test cases in Markdown format. |
exports/ |
Final TestRail-ready Excel files (.xlsx). |
test_style_guide.md |
The central source of truth for formatting, headers, and tone. |
Casely: AI-Powered QA Test Case Generator Advanced Features
- Multi-format document parsing powered by Docling integration.
- Automated style guide extraction that replicates exact column headers and ordering.
- Atomic test case generation (1 ID = 1 Scenario) to improve bug localization.
- Smart risk scoring (High, Medium, Low) and coverage tiering for sprint planning.
- Language-agnostic processing that detects and matches the language of input examples.
- Proactive workflow suggestions to guide users through the entire QA lifecycle in Openclaw Skills.
SKILL.md
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