Test design, vulnerability assessment, and quality assurance (13K skills)
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
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Generates account research briefs, personalized outreach sequences, persona-specific talk tracks, and objection handling frameworks for B2B SaaS BDR teams. Use when preparing BDR outreach for target accounts, building prospecting sequences, creating call scripts, developing objection responses, onboarding new BDRs, or reviewing outreach performance. Also use when asked to "write outreach emails," "build a prospecting sequence," "create a call script," "handle objections," or "research an account for outreach." Designed for BDR teams selling compliance, security, and GRC platforms to mid-market and enterprise buyers with multi-persona buying committees.
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Validates compliance, security, and GRC terminology in marketing copy. Enforces accurate claims, prevents common mistakes (e.g., calling SOC 2 a "certification"), and applies risk-first narrative framing for B2B SaaS audiences. Use when writing or reviewing any marketing content that references compliance frameworks, security standards, regulatory requirements, or audit processes. Also use when creating ads, landing pages, emails, case studies, or sales collateral for GRC/cybersecurity B2B SaaS products.
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Audit OpenClaw frontend code and rendered interfaces for Carapace drift, token misuse, primitive reimplementation, accessibility problems, responsive defects, and off-brand copy. Use for design reviews, compliance checks, or scheduled audit-and-fix workflows.
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自動運転モードで東京の街を走らせて画面を撮り、日本の道路交通法・道路標識令・設置基準に照らして おかしなところ（標識の向きや位置、区画線、信号、車線、速度、歩行者の動き、違反判定の誤り）を 見つけて直すループ。「AI で画面を判定して直す」「道路の見た目を法令どおりにチェック」と頼まれたとき、 または /loop で繰り返し実行するときに使う。
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Simplified Japanese web application testing skill covering unit tests, E2E tests, integration tests, Japanese text validation, IME input testing, and naming conventions. Triggers on requests for Webテスト, テスト自動化, E2Eテスト, 日本語テスト, Japanese web testing.
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Review a repository change for correctness, security, and maintainability.
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Interactive Domain-Driven Design modeling sessions based on DDD Distilled (Vaughn Vernon) and Domain Modeling Made Functional (Scott Wlaschin). Guides users through strategic and tactical design via 13 phases: discover, storming, contexts, mapping, aggregates, events, validate, glossary, workflows, types, simulate, publish, sync. Phase 13 (sync) reconciles divergences found by --analyze between the domain model and the implementation — judging whether the model or the code is authoritative, then planning and implementing the fix and re-aligning the model. Phases 9-11 take the conceptual model from phases 1-8 and produce workflow pipeline designs, compilable type definitions (TypeScript, Kotlin, Scala, Rust, C#, F#), workflow verification via type-level tests, and automatic UI field enumeration from the domain model. Phase 12 (publish) renders all docs/domain artifacts into one self-contained, cross-linked HTML site (separate files joined by a shared nav). Each phase is an interactive dialogue where AI acts as facilitator and domain expert challenger. Use when: "DDD", "ドメイン設計", "ドメインモデリング", "Event Storming", "Bounded Context", "集約設計", "ユビキタス言語", "コンテキストマップ", "ワークフロー設計", "パイプライン設計", "ステップ分割", "中間型", "型駆動フロー", "型駆動設計", "Domain Modeling Made Functional", "Railway Oriented Programming", "入力画面項目", "フォーム項目洗い出し", "UI 項目抽出", "HTMLにまとめる", "ドキュメントサイト化", "成果物を1つのHTMLに", "publish", "モデルと実装の差異", "差異解消", "実装との乖離", "モデルとコードを一致", "差異の実装計画", "sync", "複数フェーズを逐次実行", "フェーズをまとめて実行", "/ddd run", "サブコマンド一覧", "/ddd list", "/ddd", "ドメイン分析したい", "モデリングしたい", or any domain design / type modeling activity.
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Bootstrap an AI-agent skill from a TypeScript codebase by running the deterministic skillit generate/audit loop and enriching repo source (JSDoc, README, config-type properties, MCP tool annotations, examples, package.json) until the skill reaches its grade target. Use for cli, typedoc, config, or mcp (build-mode) projects; never edit SKILL.md/references directly.
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Documentation conventions for generating high-quality AI agent skills from TypeScript source. Use when preparing a library for skill generation, auditing JSDoc quality, fixing audit warnings, writing @useWhen/@avoidWhen/@never tags, or asking about documentation conventions for skills.
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Documentation conventions for generating high-quality AI agent skills from TypeScript source. Use when preparing a library for skill generation, auditing JSDoc quality, fixing audit warnings, writing @useWhen/@avoidWhen/@never tags, or asking about documentation conventions for skills. Use this even if the user just says 'audit my docs', 'improve my JSDoc', or 'make my skills better'.
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Autonomously improve an MCP skill via the skillit audit→draft→review loop (build or runtime mode) Also: skillit, refine, mcp, skill-generation, cli, audit, overlay.
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GitHub IssueまたはタスクをPlanning→実装→Review→Test→PRの全サイクルで自動実行する
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Implements BLoC (v9.x) event-driven state management for Flutter with unidirectional data flow using the flutter_bloc package. Use when implementing Bloc/Cubit classes, mapping Events to States, consuming state with BlocBuilder/BlocListener/BlocConsumer, applying event transformers (restartable/droppable/sequential) for concurrency control, setting up BlocProvider/MultiBlocProvider DI, integrating Freezed for sealed union types and exhaustive pattern matching, or testing with blocTest. Ideal for enterprise apps requiring business logic separation, precise concurrency control (search debouncing, form deduplication), or event replay debugging.
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Supabase Flutter integration for PostgreSQL, Auth, Realtime subscriptions, Storage, Edge Functions, and Row Level Security. Use when building backend features with supabase_flutter or configuring database policies.
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Expert-level guidance for Flutter production applications: architecture decisions (Clean/Layered/Hexagonal/Feature-First), advanced state management (BLoC/Riverpod/GetX), performance optimization (eliminating jank, memory profiling, reducing rebuild overhead), code review with design pattern enforcement, scalability assessments, native platform integration (MethodChannel/EventChannel/FFI), complex UI challenges (custom render objects, slivers), testing strategies (unit/widget/integration/golden), CI/CD pipeline architecture, build optimization, and accessibility compliance. Triggers: 'architecture decision', 'design pattern', 'performance issue', 'code review', 'production problem', 'scaling concerns', 'best practices', 'technical debt', 'refactoring strategy'. Essential for complex enterprise apps, critical production debugging, architectural refactors, or when choosing between competing technical approaches.
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SharedPreferences (v2.5.5) for Flutter providing simple persistent key-value storage for non-sensitive user settings and app preferences. Use this skill when storing user preferences (theme mode, language selection, font size), app settings and configuration, feature flags or A/B test assignments, simple cache data, onboarding completion status, last selected values (filters, sort options), user consent flags, or any non-sensitive data that survives app restarts. Supports String, int, double, bool, and StringList types. NOT suitable for storing tokens, passwords, API keys, or any sensitive/encrypted data (use flutter_secure_storage instead). Ideal for quick persistent storage without database overhead.
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Builds SEO-friendly web applications with Dart using the Jaspr framework. Use when creating Dart-based websites, blogs, or landing pages requiring semantic HTML output; implementing server-side rendering (SSR) or static site generation (SSG); adding Tailwind CSS via jaspr_tailwind; routing with jaspr_router; testing components with jaspr_test; or building full-stack Dart web apps where Flutter Web's canvas rendering is unsuitable.
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AI-driven Flutter E2E testing via VM Service CLI. Control running Flutter apps in debug mode for smoke tests, regression checks, exploratory testing, and UI automation. Trigger when user mentions E2E testing, UI automation, smoke tests, integration testing, test automation, controlling Flutter apps, VM Service interaction, debugging UI flows, automated regression testing, CI sanity checks, or testing native dialogs/permissions/WebViews. Supports stateful named instances or stateless direct URI connections. Ideal for rapid test feedback, AI agent workflows, element discovery, screenshot capture, log collection, and scriptable UI interactions (tap, scroll, enterText). Use for troubleshooting flaky tests, automating repetitive manual tests, verifying app behavior after merges, or setting up automated QA pipelines.
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Implements Riverpod (v3.3.x) compile-safe state management for Flutter apps. Use when implementing @riverpod code generation providers, handling AsyncValue loading/error/data states, using ref.watch/ref.read/ref.listen, setting up ProviderScope, writing Notifier/AsyncNotifier classes, using FutureProvider/StreamProvider, applying autoDispose and family modifiers, combining providers, testing providers in isolation, scoping rebuilds with Consumer instead of ConsumerWidget, using ref.watch with select() for field-level precision, migrating from StateNotifierProvider or Riverpod 2.x patterns, handling Notifier resource lifecycle with ref.onDispose, or using experimental Mutation and offline persistence APIs.
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Covers Flutter testing across all three layers: unit tests (business logic, ViewModels, repositories), widget tests (UI rendering, interactions, golden regression), and integration/E2E tests (full app flows, native OS interactions). Use this skill when writing any Flutter test, setting up mocking with mocktail or mockito, implementing golden file tests, debugging async failures (pumpAndSettle timeouts, Timer leaks, FakeAsync deadlocks), fixing cross-platform golden pixel diffs in CI/CD, testing state management (Riverpod/BLoC/Provider), handling permission dialogs or native system UI with Patrol, or troubleshooting MediaQuery/Theme missing errors in widget tests.
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Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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Break a user interface under real-world conditions across responsiveness, hostile content, interaction states, accessibility, network failure, interruption, and complete user journeys, reporting observable user harm with evidence rather than aesthetic opinion. Use whenever the user wants to stress-test a UI, verify responsive and edge-case behaviour, inspect loading/error/empty/recovery states, review a flow for friction, or find where an interface fails under reality. Part of the audit suite; inherits the shared constitution while its own job is proving observable user harm.
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Evidence-driven application audit protocol for security, authorization, privacy, concurrency, state integrity, reliability, performance, accessibility, visual consistency, responsive behavior, and release readiness. Use for incremental checks, pre-merge review, pre-launch audits, high-stakes deep audits, AI-generated code review, hardening, or release-gate design. Prefer this protocol over ad-hoc review when the user asks whether software is safe or ready to ship.
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