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概要と使いどころ
Document-code change notification system: traceable doc-code binding via git tree hash, git-diff-driven reconciliation plans with confidence/risk metadata, and idempotent execution. Use when maintaining documentation freshness, detecting stale docs, or binding docs to source 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。
設計ドキュメントに基づいて実装計画を生成します。ScalarDB特有のスキーマ定義、トランザクション実装、統合テストを含む実装可能なタスク指示書を作成し、フェーズ別の実装ロードマップを提供します。
Turn any URL — landing page, blog post, product page, documentation page, changelog, public PDF, or web article — into a finished AI-generated video using the Ozor MCP. Use this skill whenever the user gives a link and wants a video from its content: 'make a video from this URL', 'video from my landing page', 'turn this blog post into a video', 'video from https://...', 'video from our homepage', 'generate a video from this product page', 'create a video from this article'. This skill runs analyze_document with the url parameter (no scraping needed on our side), presents the resulting plan to the user, then generates → exports → embeds. Do NOT use this skill for a short text brief (use ozor-generate) or for an attached local file (use ozor-document-video).
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 designing, implementing, migrating, and debugging SwiftData persistence in Swift and SwiftUI apps. Use when working with @Model schemas, @Relationship/@Attribute rules, Query or FetchDescriptor data access, ModelContainer/ModelContext configuration, CloudKit sync, SchemaMigrationPlan/history APIs, ModelActor concurrency isolation, or Core Data to SwiftData adoption/coexistence.
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。
Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload pipelines.
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。
When the user wants to plan or optimize paid user acquisition campaigns. Also use when the user mentions "Apple Search Ads", "user acquisition", "paid ads", "UA", "ad campaign", "install campaign", "Facebook ads for apps", "TikTok ads", or "cost per install". For organic growth, see aso-audit. For launch-specific UA, see app-launch.
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。
When the user wants to create, plan, or optimize App Store In-App Events — the event cards that appear on the Today tab, search results, and your product page. Use when the user mentions "in-app event", "App Store event", "event card", "Today tab", "live event", "challenge", "game event", "seasonal event card", or wants visibility beyond organic search. For general ASO, see aso-audit. For seasonal keyword strategy, see seasonal-aso.
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 and migrate tests using the Swift Testing framework with @Test, @Suite, #expect, #require, confirmation, parameterized tests, test tags, traits, withKnownIssue, XCTest UI testing, XCUITest, test plan, mocking, test doubles, testable architecture, snapshot testing, async test patterns, test organization, and test-driven development in Swift. Use when writing or migrating tests with Swift Testing framework, implementing parameterized tests, working with test traits, converting XCTest to Swift Testing, or setting up test organization and mocking 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。
Integrate and optimize Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodelc, .mlpackage), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model performance.
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。
Analyze Swift and mixed-language compile hotspots using build timing summaries and Swift frontend diagnostics, then produce a recommend-first source-level optimization plan. Use when a developer reports slow compilation, type-checking warnings, expensive clean-build compile phases, long CompileSwiftSources tasks, warn-long-function-bodies output, or wants to speed up Swift type checking.
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。
Apply approved Xcode build optimization changes following best practices, then re-benchmark to verify improvement. Use when a developer has an approved optimization plan from xcode-build-orchestrator, wants to apply specific build fixes, needs help implementing build setting changes, script phase guards, source-level compilation fixes, or SPM restructuring that was recommended by an analysis 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。
Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Use when a user asks to refactor many files, split workstreams, analyze a target code area, and coordinate sub-agents with clear ownership and dependency-aware execution.
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。
Translate Figma designs into production-ready SwiftUI code with 1:1 visual fidelity using the Figma MCP workflow. Trigger when the user provides Figma URLs or node IDs and wants iOS/SwiftUI implementation, asks to implement a design or component from Figma for an iOS app, or references Figma selections in the context of an Xcode/SwiftUI project. Also trigger when user asks to inspect Figma designs for iOS planning, fetch design tokens for SwiftUI, or convert Figma assets for Xcode. Requires a working Figma MCP server connection. Do NOT trigger for web/React implementations.
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。
Run a 3-leg evaluation against a newly released LLM. Leg 1 is trap questions with deterministic answers, leg 2 is an agentic orchestration task with a planted failure, leg 3 is a brownfield feature build in a real repo. Use when the user wants to vibe-check, test, evaluate, or compare a new frontier model, or mentions model-bench, model vibe check, or launch-day protocol.
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。
Stress-tests ideas by surfacing assumptions, counterarguments, and confidence gaps. Use when evaluating claims, proposals, plans, or decisions that need rigorous intellectual scrutiny.
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。
Generates IEEE-format LaTeX technical reports from project requirements and codebase evidence, using academic prose, pseudocode-only explanations, BibTeX references, and IEEEtran formatting.
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。
Plan and execute Convex schema migrations safely, including adding fields, creating tables, and data transformations. Use when schema changes affect existing data.
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。
Plans Convex schema and data migrations with widen-migrate-narrow and @convex-dev/migrations. Use for breaking schema changes, backfills, table reshaping, or zero-downtime rollouts.
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。
Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality 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。
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.
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。
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
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。
A relentless interview to sharpen a plan or design.
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。
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