browse-qa
QA a web or app feature from a ticket, URL, acceptance criteria, or plain-language description, then generate reusable browse flows for regression coverage. Uses the `browse` skill for the actual browser or simulator interaction and keeps the QA loop focused on scenarios, evidence, and report quality.
What this skill does
<EXTREMELY-IMPORTANT> This skill owns the QA plan and report, not the low-level browser command encyclopedia. Non-negotiable rules: 1. Turn the incoming spec into explicit scenarios before testing. 2. Confirm ambiguous targets or platforms before execution. 3. Use the `browse` skill for actual browser or simulator interaction. 4. Capture evidence for each failed or important scenario. 5. Save rerunnable flows only when they are cleanly scoped and valuable for regression. </EXTREMELY-IMPORTANT> # browse-qa ## Inputs - `$request`: Ticket, URL, app target, acceptance criteria, or plain-language QA request ## Goal Produce a credible QA run that: - turns a vague request into explicit scenarios - runs those scenarios against the real target - captures evidence for passes and failures - saves rerunnable browse flows when appropriate - returns a clean QA report the user can act on ## Step 0: Resolve the target and spec Work out: - what feature is being tested - the platform: web, iOS simulator, Android emulator, or macOS app - the target URL, build artifact, or app identifier - the acceptance criteria or expected outcomes If the target or platform is ambiguous, ask before testing. **Success criteria**: The QA target and acceptance criteria are explicit. ## Step 1: Build the scenario list Break the request into: - happy path - validation or error path - edge cases - exploratory probes worth trying after the stated acceptance criteria Keep the plan small enough to execute in one session unless the user asked for a broad QA sweep. **Success criteria**: There is a concrete scenario list with expected outcomes. ## Step 2: Execute with the `browse` skill Use `Skill` to invoke `browse` for: - navigation - page stabilization - interactive element discovery - clicks, fills, and submissions - screenshots, console logs, and network inspection Rules: - keep the same browse session for one logical user journey unless isolation is intentional - use headed or handoff mode only for real blockers like CAPTCHA, MFA, or OAuth walls - save screenshots and flow artifacts under the browse session directories **Success criteria**: Each scenario is executed against the real target with enough evidence to judge pass or fail. ## Step 3: Record reusable regression flows When the scenario is stable and worth rerunning: - record the flow - split unrelated user journeys into separate flow files - give each saved flow a descriptive name Do not save noisy or half-manual recordings as regression artifacts. **Success criteria**: Saved flows are independently rerunnable and map to clear scenarios. ## Step 4: Report results For each scenario, record: - expected result - actual result - pass or fail - evidence such as screenshot path, console error, or network symptom Also report: - exploratory findings - regression flow files created - blockers that prevented full verification **Success criteria**: Another engineer can understand the QA outcome without replaying the whole session first. ## Guardrails - Do not duplicate the full browse command manual inline; use the `browse` skill. - Do not guess a platform when the request is ambiguous. - Do not save low-signal flows just to say a regression asset was created. - Do not add `disable-model-invocation`; QA should stay available when the user asks for it. - Do not add `context: fork`; results are usually needed in the current execution flow. ## Output Contract Report: 1. target tested 2. scenarios executed 3. pass/fail result for each scenario 4. evidence captured 5. regression flow files created 6. blockers or uncovered gaps
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