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NOTE: Sorry about the video quality — I accidentally messed up the conversion and everything came out blurry. The content is all there, just squint a little. I will fix it in future videos. AI QA Workflow is an open-source toolkit that connects AI code agents like Cursor, Claude, and Claude Code with test management systems. Using slash commands and MCP integrations, it automates the full QA lifecycle — from tracing requirements in Jira, to planning tests, designing test cases, syncing them to TestLink, and even generating demo presentations. The Problem with v1.0: In version 1.0, three command files totaled over 2,200 lines. The AI would start strong but lose track halfway through — mixing up steps, referencing wrong sections, and producing inconsistent test cases. Long context kills accuracy. What Changed in v2.0: The three monolithic files were broken into small, focused commands. Each command does exactly one job and ends with a clear next step. Jira Trace Pipeline: 1 entry point → 3 sub-commands (fetch → structure → document) Test Workflow: 2 large files → 13 focused commands with built-in review steps Demo Pipeline: content generation → review → PowerPoint → email announcement TestLink Sync: smart diff — skips unchanged cases, creates new ones, updates modified ones New in v2.0: Test plan review command (coverage matrix + gap analysis) Test case review command (objective clarity, step specificity, measurable results) Smart TestLink sync (git-diff style comparison for test management) Demo presentation pipeline MCP Server Integrations Covered: Jira MCP TestLink MCP (custom-built) Playwright MCP (browser automation for GUI testing) FreeRADIUS SQL MCP (authentication/accounting) WPA Supplicant MCP (wireless client control) Installation: git pull make install Installs slash commands to both Claude Code and Cursor. Repository: https://github.com/dogkeeper886/ai-qa... #QA #AI #TestAutomation #ClaudeCode #Cursor #MCP #Jira #TestLink #OpenSource #DevTools #QualityAssurance