Generate structured QA test plans for game development sprints.
npx skills add https://github.com/johnatas-henrique/overdrive --skill qa-plan-johnatas-henrique
Please help me install this Agent Skill. Skill: qa-plan Source: https://github.com/johnatas-henrique/overdrive/tree/main/.opencode/skills/qa-plan Command: npx skills add https://github.com/johnatas-henrique/overdrive --skill qa-plan-johnatas-henrique
Manually creating QA test plans for game development sprints is time-consuming, inconsistent, and often misses critical test coverage for edge cases, regression risks, and acceptance criteria. This skill automates the entire process, ensuring comprehensive, traceable test plans that align with your team's definition of done.
production/sprints/ so developers and QA know exactly what to test before implementation begins.Use the qa-plan skill to generate a structured QA test plan for your current game development sprint.
High-intent search queries and answers about installing and using this skill.
Generate a structured QA test plan by parsing story files, GDDs, and architecture documents to classify user stories by test type and define automated and manual test requirements. This produces actionable test specifications aligned with acceptance criteria.
Automated story classification reads sprint or story files and categorizes each by test type, such as Logic, Integration, Visual/UI, or Config/Data. It uses acceptance criteria and referenced GDDs to ensure accurate test coverage.
Align manual testing checklists with definition of done by extracting GDD formulas, edge cases, and acceptance criteria from sprint documents. This produces structured QA plans covering manual checklists, smoke test scopes, and playtest sign-off requirements.
Yes, QA planning works directly with existing GDD and architecture documents by parsing them to extract formulas and edge cases. It uses these documents to classify user stories and generate traceable test specifications.
Yes, you can define both automated and manual test requirements by parsing user story files and classifying them by test type. The process extracts acceptance criteria to produce actionable test specifications and smoke test scopes.
The best way to ensure gap-free test coverage is to automate the extraction of GDD formulas, edge cases, and acceptance criteria from story files. This generates structured test plans that align testing work with the definition of done.
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