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Analyze a Coval adversarial / red-team testing report and turn it into an agent-hardening plan. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or a per-scenario scorecard from an adversarial sweep and wants evidence-backed next steps such as prompt/guardrail changes, refusal hardening, verification fixes, escalation routing, or expanded attack coverage.
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Trial protocol for teaching AI Matrx an expert's knowledge until the platform breaks, fixing it. Use when asked to run an expertise trial, distil a person/creator/recent video into a Masterwork, or test the capture product. NOT for a known-missing feature (use build-sub-feature).
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Real tests: a fresh agent walks the live product against sealed checks proven to catch a planted break. Use when told to use safety-net, to check whether an area really works now, or around a change too wide for one agent to see every break. NOT for one automated test (use forcing-function-tests).
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The bar every automated test or guard must clear: green only when the real system works. Use when writing, fixing, or reviewing a test, mock, stub, fixture, snapshot, or self-test; adding a regression test for a bug; or about to call work done because tests pass.
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A test skill for e2e testing
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Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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Test2::V0、Test::More、proveランナー、モッキング、Devel::Coverによるカバレッジ、TDD方法論を使用したPerlテストパターン。
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ユニットテスト、統合テスト、非同期テスト、プロパティベーステスト、モック、カバレッジを含むRustテストパターン。TDD方法論に準拠。
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Kotest、MockK、コルーチンテスト、プロパティベーステスト、Koverカバレッジを含むKotlinテストパターン。イディオマティックなKotlinプラクティスによるTDD方法論に従う。
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テーブル駆動テスト、サブテスト、ベンチマーク、ファジング、テストカバレッジを含むGoテストパターン。イディオマティックなGoプラクティスによるTDD方法論に従う。
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pytest、TDD方法論、フィクスチャ、モック、パラメタライズ、カバレッジ要件を使用したPythonテスト戦略。
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AI支援開発のためのリグレッションテスト戦略。データベース依存なしのサンドボックスモードAPIテスト、自動バグチェックワークフロー、同一モデルがコードの作成とレビューを行う際のAIの盲点を検出するパターン。
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PlaywrightのE2Eテストパターン、Page Objectモデル、設定、CI/CD統合、アーティファクト管理、フレーキーテスト戦略。
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C++テストの作成・更新・修正、GoogleTest/CTestの設定、失敗やフレーキーテストの診断、カバレッジ/サニタイザーの追加時にのみ使用。
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Evaluate design from a UX perspective, assessing visual hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with quantitative scoring, persona-based testing, and actionable feedback. Use when the user asks to review, critique, evaluate, or give feedback on a design or component.
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Generates test doubles (Mocks, Stubs, Fakes, Spies) for PHP 8.5. Creates appropriate double type based on testing needs with PHPUnit MockBuilder patterns.
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Use after implementing features - verifies each acceptance criterion with structured testing and posts verification reports to the GitHub issue
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Generates PSR-20 Clock implementation for PHP 8.5. Creates ClockInterface implementations including SystemClock, FrozenClock, and OffsetClock for time abstraction and testing. Includes unit tests.
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Generates InMemory repository implementations for PHP 8.5 testing. Creates fake repositories with array storage, supporting CRUD operations and queries without database.
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Use when explaining concepts at different expertise levels, moving between abstract principles and concrete implementation, identifying edge cases by testing ideas against scenarios, designing layered documentation, decomposing complex problems into actionable steps, or bridging strategy-execution gaps. Invoke when user mentions abstraction levels, making concepts concrete, or explaining at different depths.
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Turn vague Acceptance Criteria into measurable checks and test assertions
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Implement state machines with AASM for workflow management. Covers state transitions, guards, callbacks, and testing.
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Use when designing experiments for subject lines, offers, cadences, or journeys.
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全面的AB测试分析工具，支持实验设计、统计检验、用户分群分析和可视化报告生成。用于分析产品改版、营销活动、功能优化等AB测试结果，提供统计显著性检验和深度洞察。
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