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Found 56 Skills
AI SDLC test-case-driven testing workflow. Use when an AI assistant is asked to derive test cases, create a test plan, expand coverage, or write tests from explicit scenarios before implementing unit, service, transport, or integration tests. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.
Use after QA strategy and test-case synthesis to build the requirements-to-test traceability matrix, identify missing coverage and test blockers, and score readiness for QA execution. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.
Website exploration for testing using Playwright MCP
TestRail integration. Manage data, records, and automate workflows. Use when the user wants to interact with TestRail data.
Generates eval test cases from an eval suite plan (output of /eval-suite-planner) or a plain-English agent description. Supports both single-response and conversation (multi-turn) evaluation modes. Outputs a Copilot Studio test set table, a CSV file for import (single-response only), and a docx report for human review.
Sync tests with TestRail. Use when user mentions "testrail", "test management", "test cases", "test run", "sync test cases", "push results to testrail", or "import from testrail".
Derive security requirements from threat models and business context. Use when translating threats into actionable requirements, creating security user stories, or building security test cases.
Use when you need to actually write inspection script code and implement an automation checker based on the design scheme of assess-automation-checklist; output runnable script files and integration guides. Trigger words: write inspection script, implement automatic inspection, code checker, write checker code.
Pairwise test generation
Eval enablement accelerator — help customers think through "what does good look like" for their AI agent, then generate a structured eval plan and test cases they can use immediately. No running agent required. Works from a description, an idea, or even a vague goal. Use when anyone mentions agent evaluation, eval planning, "what should we test", "how do we know if the agent is good", test case generation, or interpreting eval results.
Add a test case to the web renderer
Design test strategies and test plans. Trigger with "how should we test", "test strategy for", "write tests for", "test plan", "what tests do we need", or when the user needs help with testing approaches, coverage, or test architecture.