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Scan, connect, and communicate with Bluetooth Low Energy peripherals and publish local peripheral services using Core Bluetooth. Use when implementing BLE central or peripheral roles, discovering services and characteristics, reading and writing characteristic values, subscribing to notifications, configuring background BLE modes, restoring state after app relaunch, or working with CBCentralManager, CBPeripheral, CBPeripheralManager, CBService, CBCharacteristic, CBUUID, or Bluetooth Low Energy workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Modern Swift concurrency with async/await, actors, TaskGroup, Sendable, and proper actor isolation for thread-safe iOS development

日本語の概要は準備中です。原文の説明を表示しています。

Expert guidance on Swift Testing best practices, patterns, and implementation. Use when developers mention: (1) Swift Testing, @Test, #expect, #require, or @Suite, (2) "use Swift Testing" or "modern testing patterns", (3) test doubles, mocks, stubs, spies, or fixtures, (4) unit tests, integration tests, or snapshot tests, (5) migrating from XCTest to Swift Testing, (6) TDD, Arrange-Act-Assert, or F.I.R.S.T. principles, (7) parameterized tests or test organization.

日本語の概要は準備中です。原文の説明を表示しています。

Scan Apple's SwiftUI documentation for deprecated APIs and update the SwiftUI Expert Skill with modern replacements. Use when asked to "update latest APIs", "refresh deprecated SwiftUI APIs", "check for new SwiftUI deprecations", "scan for API changes", or after a new iOS/Xcode release. Requires the Sosumi MCP to be available.

日本語の概要は準備中です。原文の説明を表示しています。

Write, review, or improve SwiftUI code following best practices for state management, view composition, performance, macOS-specific APIs, and iOS 26+ Liquid Glass adoption. Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Expert guidance for Swift Testing: test structure, #expect/#require macros, traits and tags, parameterized tests, test plans, parallel execution, async waiting patterns, and XCTest migration. Use when writing new Swift tests, modernizing XCTest suites, debugging flaky tests, or improving test quality and maintainability in Apple-platform or Swift server projects.

日本語の概要は準備中です。原文の説明を表示しています。

Diagnose data races, convert callback-based code to async/await, implement actor isolation patterns, resolve Sendable conformance issues, and guide Swift 6 migration. Use when developers mention: (1) Swift Concurrency, async/await, actors, or tasks, (2) "use Swift Concurrency" or "modern concurrency patterns", (3) migrating to Swift 6, (4) data races or thread safety issues, (5) refactoring closures to async/await, (6) @MainActor, Sendable, or actor isolation, (7) concurrent code architecture or performance optimization, (8) concurrency-related linter warnings (SwiftLint or similar; e.g. async_without_await, Sendable/actor isolation/MainActor lint).

日本語の概要は準備中です。原文の説明を表示しています。

Refactor and review SwiftUI view files with strong defaults for small dedicated subviews, MV-over-MVVM data flow, stable view trees, explicit dependency injection, and correct Observation usage. Use when cleaning up a SwiftUI view, splitting long bodies, removing inline actions or side effects, reducing computed `some View` helpers, or standardizing `@Observable` and view model initialization patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Modern SwiftUI patterns for iOS 18+, including @Observable, navigation, state management, and view composition following SOLID principles

日本語の概要は準備中です。原文の説明を表示しています。

Build, refactor, or review macOS menubar apps that use Tuist and SwiftUI. Use when creating or maintaining LSUIElement menubar utilities, defining Tuist targets/manifests, implementing model-client-store-view architecture, adding script-based launch flows, or validating reliable local build/run behavior without Xcode-first workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Applies a modern CSS reset covering box-sizing, margin removal, text rendering, media defaults, and root stacking context. Use when starting a new web project, creating a global stylesheet, or when the codebase lacks sensible CSS defaults.

日本語の概要は準備中です。原文の説明を表示しています。

Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-review.

日本語の概要は準備中です。原文の説明を表示しています。

Structured 3-phase peer review of a diff or PR — intent, issues by severity, then pointed merge-readiness questions and a verdict. Use for general code review. Not for AI workflow self-fix-and-edit (ai-systems-review) or no-edit devil's-advocate threat models (adversarial-challenge). Phase 3 asks questions only; it is not the adversarial-challenge skill.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when the user asks how to "use VibeTags", "add VibeTags annotations", "set up AI guardrails", "protect code from AI", "configure AI platforms", asks about @AILocked, @AIContext, @AIDraft, @AIAudit, @AIIgnore, @AIPrivacy, @AICore, @AIPerformance, @AIContract, @AITestDriven, @AIThreadSafe, @AIImmutable, @AIDeprecated, @AIObservability, @AIRegulation, @AIArchitecture, @AILegacyBridge, @AIStrictClasspath, @AIInternationalized, @AIPublicAPI, @AISchemaSafe, @AIStrictExceptions, @AIStrictTypes, @AIParallelTests, @AIIdempotent, @AIFeatureFlag, @AISecure, @AICallersOnly, @AISandboxOnly, @AIMemoryBudget, @AIPure, @AIDomainModel, @AIExtensible, @AIInputSanitized, @AISecureLogging, @AIExplain, @AIPrototype, @AISunset, @AITemporary annotations, or wants to control how AI tools interact with Java code.

日本語の概要は準備中です。原文の説明を表示しています。

Build reactive, type-safe, production-grade backends. ALWAYS use this skill when the user asks to build, plan, design, or implement backend features, APIs, data models, server logic, database schemas, web apps, full stack apps, or mobile apps. This includes planning and architecture discussions.

日本語の概要は準備中です。原文の説明を表示しています。

Guide for evaluation — inline evaluators, Inspect AI integration, and custom evaluators for measuring training progress. Use when the user asks about evaluation, metrics, benchmarks, or how to measure model quality during training.

日本語の概要は準備中です。原文の説明を表示しています。

Guide for using renderers — the bridge between chat-style messages and token sequences. Covers renderer setup, TrainOnWhat, vision inputs, model family matching, and custom renderers. Use when the user asks about renderers, tokenization, message formatting, or vision inputs.

日本語の概要は準備中です。原文の説明を表示しています。

Guide for hyperparameter selection — learning rate formulas, LoRA rank, batch size, group size, schedules, and model-specific tuning. Use when the user asks about learning rate, batch size, hyperparameter tuning, or how to configure training parameters.

日本語の概要は準備中です。原文の説明を表示しています。

Behavioral guardrails for implementation work. Reduces common LLM coding mistakes: overcomplication, silent assumption-picking, scope drift, and unverifiable success criteria. Load on Builder and software-engineer-mode.

日本語の概要は準備中です。原文の説明を表示しています。

Use when: 'do work', 'dispatch builder', or team lead triggers automated task implementation. Governs end-to-end flow from dispatch through verification, fail handling, batch mode, and escalation.

日本語の概要は準備中です。原文の説明を表示しています。

Use when: ticket lifecycle, state transitions, ready for QA, changes requested, QA passed, role-based workflow policy, Developer to QA handoff, or relay routing across delivery agents.

日本語の概要は準備中です。原文の説明を表示しています。

Use when: implement a scoped ticket, fix a bug, add tests, prepare a PR-ready code change, or reuse a standard builder workflow across software engineer agents.

日本語の概要は準備中です。原文の説明を表示しています。

Use when: reviewing or producing any external-facing prose — ADRs, proposals, GitHub comments, Telegram messages, cover letters, client drafts, or planner-mode wording. Removes AI-tell patterns and raises writing quality before output leaves the team.

日本語の概要は準備中です。原文の説明を表示しています。

Master orchestrator for the 5-step productivity loop. Runs audit, architect, analyst, refinery, and compounder in sequence or individually. Use when you want to run the full loop, start the system, check system status, resume from where you left off, or run a specific step. Manages state, sequencing, and skill chaining. Supports full loop, single step, resume, and status-only modes.

日本語の概要は準備中です。原文の説明を表示しています。