QA Autopilot
Automates the generation of Jira/Xray test cases by integrating Jira knowledge with Google Gemini's AI capabilities.
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The QA Autopilot addresses the tedious and time-consuming process of manual test case creation in Jira. Inspired by the Model Context Protocol (MCP) concept, this command-line tool acts as a smart bridge: it connects to Jira to extract full context from a user story, sends this information to Google Gemini (via Vertex AI) with a QA-focused prompt, and then generates a detailed set of Gherkin-formatted test cases. Finally, it automatically creates these test cases as 'Test' issues in Jira/Xray, linking them to the original user story. This empowers QA analysts to focus on strategic tasks like exploratory testing and risk analysis, as they only need to review, adjust, and approve the AI-generated cases.
Características Principales
- Connects Jira (as knowledge server) with Google Gemini (Vertex AI) for test case generation.
- 3 GitHub stars
- Generates detailed test cases in Gherkin format based on AI analysis.
- Extracts comprehensive context (description, acceptance criteria) from Jira user stories.
- Automatically creates 'Test' issues in Jira/Xray and links them to the original user story.
- CLI-driven for simple execution with a Jira User Story ID.
Casos de Uso
- Reducing manual effort and saving time for QA analysts in test case documentation.
- Automating the creation of test cases for new or updated Jira user stories.
- Streamlining the QA process by integrating AI-powered test generation into existing Jira workflows.
