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Review a feature or proposal from four perspectives: product management, architecture, development, and quality assurance. Get each role’s concerns and first actions, followed by a summary of shared priorities and unresolved disagreements.
Fix iOS bugs by editing source code, rebuilding the app, deploying it again, and verifying the result on a real device. Preserve a state snapshot as test data to help detect recurrence.
Create acceptance criteria and a manual validation plan for feature changes. Cover successful flows, unusual inputs, failures, and performance limits, with observable outcomes and clear evidence requirements so reviewers can decide whether each criterion passes.
Test omo Codex Light edition in an isolated environment using real Codex and a local mock model. Verify installation, plugin hooks, and terminal startup, with captured evidence and no calls to a real model API.
Remove AI-generated patterns from QA reports, bug reports, test summaries, status updates, and quality communications. Detects and rewrites robotic test-result language, template-sounding status updates, inflated severity descriptions, and generic stakeholder reports — without inventing facts. Makes QA writing sound like a real engineer wrote it. Use when: "humanize report," "rewrite QA summary," "fix test report," "make this sound human," "clean up status update." Not for: general prose, blog, or marketing-copy cleanup — use the global humanizer skill. Not for: classifying or routing CI failures — use ai-bug-triage. Related: ai-bug-triage, qa-metrics, qa-dashboard, quality-postmortem.
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Move quality earlier in the development lifecycle. Covers dev/QA pairing patterns, Three Amigos sessions, TDD facilitation (Red-Green-Refactor), PR review checklists for testability, and Definition of Done with quality gates. Includes shift-left maturity model for team assessment. Use when: "shift left," "TDD," "dev-QA pairing," "definition of done," "testability," "quality culture," "QA in sprint planning." Not for: writing the unit tests themselves — use unit-testing; automated PR test-quality review at scale — use ai-qa-review; multi-quarter QA direction or roadmap — use test-strategy. Related: unit-testing, ai-qa-review, test-strategy.
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The systematic discipline of reviewing AI-generated and human-written marketing content for quality, accuracy, consistency, and effectiveness. This isn't proofreading—it's strategic quality control that catches issues before they damage brand, waste spend, or miss opportunities. In an era where AI can generate content at scale, QA becomes the bottleneck— and the moat. Speed without quality is just fast failure. Every piece of content is a brand promise, and QA ensures that promise is kept. Content QA operates at multiple levels: tactical (spelling, grammar), strategic (message alignment), technical (platform compliance), and brand (voice, tone). The best QA catches what the creator couldn't see because they were too close. Use when "review content, QA, quality check, proofread, check copy, content review, brand compliance, verify content, fact check, review before publish, content approval, final review, qa, content-review, quality-assurance, brand-compliance, proofreading, content-quality, review" mentioned.
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Post-implementation QA planning — independent of /review (the developer chooses whether to run them sequentially or in parallel), only when the change has a running surface worth driving. Interviews the developer to turn the specs and the diff into an executable QA specification (specs/qa/QA-<N>-<slug>.md) that /execute-qa runs. The agent drives browser and shell; the human steps in only at named handoff points. Use only when the user asks to plan manual QA — never trigger automatically.
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Executes a QA specification (specs/qa/QA-<N>-<slug>.md) written by /plan-qa: drives every step with the plan's drivers, verifies each Expected line mechanically ([assert]) or by evidence-backed judgment against the plan's written criterion ([judge]), pauses at named operator handoffs, and writes the results artifact QA-RESULTS-<N>-<slug>.md. Use only when the user asks to run or execute a QA plan — never trigger automatically.
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This skill should be used when the user says "找 bug" / "看一下有没有 bug" / "smart-qa" / "/smart-qa" / "帮我测一下这个项目" / "智能 QA" / "推断业务流程测一下"，or asks for an autonomous bug-hunt where they DON'T already know what to test. Distinct from `qa` (blind exploration) and `devtest` (verifies a specific change). smart-qa READS the project source — prefers PRD/requirements docs, falls back to code (activities, routes, click handlers, API calls) — then proposes a focused test plan for confirmation before driving the app. v1 stops after the user confirms the plan and hands off to the existing `qa` skill for execution. v2 (planned) adds per-step assertions.
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Draft the QA scope and plain-language Given/When/Then test scenarios for a Jira ticket, built from the full ticket, the decisions made in its comments, and the actual code change read commit by commit (open PR, the ticket's merged PR, the branch against its base, or a named commit range). Saves a Markdown draft under docs/, iterates with the user, then posts it to the ticket as a new Jira comment only after explicit approval. Use on "QA scope for PROJ-123", "what should QA test", "write test scenarios for QA", "hand this ticket to QA", "prep the QA handoff", "gherkin scenarios for this ticket", or when a branch is ready for manual testing — even when the user only names the ticket or says "this branch".
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テストケースの実行制御を行うフェーズスキル。各テストケースを qa-runner → qa-judge のパイプラインで実行し、アプリ状態管理と結果収集を担当する。ios-qa-workflow から参照される。
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QA テストスイートの解析・前提条件解決・実行計画策定を行うフェーズスキル。ios-qa-workflow から参照される。「テスト計画」「QA 準備」「テストスイート解析」などのキーワードで自動適用。
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AI QA Agent のメインオーケストレーター。テストスイートまたは個別テストケースの QA を段階的に実行する。フェーズスキルに委譲して段階的開示を行い、サブエージェントでコンテキスト隔離を実現する。「QA」「動作確認」「テストケース実行」「smoke test」「E2E」「手動テスト」「結合テスト」などのキーワードで自動適用。
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QA テスト結果を集約し、構造化レポートを生成するフェーズスキル。失敗テストの分析と次のアクション提案を含む。「QA レポート」「テスト結果」「QA 結果」などのキーワードで自動適用。
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Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to "qa", "QA", "test this site", "find bugs", "test and fix", or "fix what's broken". Proactively suggest when the user says a feature is ready for testing or asks "does this work?". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary. For report-only mode, use /qa-only. (gstack) Voice triggers (speech-to-text aliases): "quality check", "test the app", "run QA".
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Test websites and web apps in a real cloud browser, including local development servers. Check a specific user journey or several flows, then receive a quality score from 1 to 5 with evidence and identified issues.
Check a Twenty pull request through real browser scenarios derived from its changes. Verify database effects and server logs alongside visible results, then produce screenshots, a structured verdict, and a report of any failures or uncertainty.
Build and optimize quantum circuits with PennyLane, including models that combine quantum circuits with PyTorch or JAX. Explore molecular energy estimation and optimization problems, validate values and gradients in simulation, and prepare tested circuits for provider plugins.
Build an end-to-end evaluation pipeline for Python AI applications using pixie-qa and real language-model calls. Define criteria, prepare realistic test data, score application runs, and analyze the evidence to produce a prioritized improvement plan.
Test a web application using branch changes, selected pages, or the whole app as scope. Choose among three testing levels, document issues with evidence, fix them in separate commits, and verify results in a release-readiness report.
Read and control Aqara smart home devices: plugs, switches, lights, AC, locks, curtains, scenes. Trigger phrases: aqara, aqara hub, aqara lock, aqara curtain.
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Produce a multi-quarter QA strategy document. Covers scope, risk-based prioritization, test levels (unit/integration/E2E), pyramid analysis, entry/exit criteria, quality KPIs, tool selection rationale, CI scaling levers, and timeline planning. Output is an actionable strategy document, not a shelf document. Use when: "test strategy," "QA strategy doc," "testing approach," "QA roadmap," "multi-quarter QA direction." Not for: a single-sprint or single-release plan — use test-planning. Not for: identifying which areas carry the most risk — use risk-based-testing first. Related: risk-based-testing, qa-metrics, release-readiness, test-planning, test-reliability.
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Build and visualize QA dashboards and reports with Allure Report, Grafana, and ReportPortal. Covers test execution visualization, stakeholder-facing quality reports, trend/flakiness panels, release-readiness gates, alerting, and CI integration for automated report generation. Use when: "test dashboard," "Allure," "test report," "quality dashboard," "Grafana," "ReportPortal," "test results visualization." Not for: defining which KPIs to measure or how to interpret them — use qa-metrics (this skill builds the panels; qa-metrics decides what they should show). Related: qa-metrics, ci-cd-integration, ai-bug-triage.
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