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概要と使いどころ
Separates audio tracks into individual stems (vocals, drums, bass, other) using Meta's Demucs neural network model via the demucs Python package. Supports batch processing of WAV and MP3 files, outputs isolated stems in FLAC or WAV format, and integrates with FFmpeg for format conversion and loudness matching post-separation.
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Details Paraglide.js i18n 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。
Concurrent investigation of independent failures. Use when multiple unrelated issues need parallel resolution.
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Fuzz directories, files, and parameters using ffuf, feroxbuster, arjun, paramspider, and x8. Use when the user has live hosts and needs to find hidden routes, backup files, exposed configs, and untracked URL parameters.
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Local speech-to-text on Apple Silicon with two cross-checking MLX engines: NVIDIA Parakeet TDT v2 (parakeet-mlx) and Qwen3-ASR 1.7B (mlx-audio, hotword biasing). Batch JSONL with word timestamps, confidence, provenance, and an agreement verdict. No NeMo or PyTorch. Use when transcribing audio files, identifying game or legacy voice clips by content, telling speech from SFX, serving an OpenAI-compatible STT endpoint, or dictating. For push-to-talk into any text field, use the Handy app.
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This skill should be used when the user asks to "make an ASCII animation", "build a terminal/CLI intro or loader", "convert an image or video to ASCII art", "add an ASCII shader/post-effect to a canvas or Three.js scene", "create retro/hacker text-character motion", or "animate text characters with a brightness ramp". Covers generative ASCII fields, image/video/3D-to-ASCII, and animated character art for both web and terminal.
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Plan a comprehensive spectroscopic analysis campaign by defining the analytical question, assessing sample characteristics, selecting appropriate techniques using a decision matrix, planning sample preparation for each technique, sequencing analyses from non-destructive to destructive, and defining success criteria with a cross-validation strategy.
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Generate jigsaw puzzles via generate_puzzle() or geom_puzzle_*() with parameter validation against inst/config.yml. Supports rectangular, hexagonal, concentric, voronoi, and snic puzzle types with configurable grid, size, seed, offset, and layout parameters. Use when creating puzzle SVG files for a specific type and configuration, testing generation with different parameters, generating sample output for documentation or demos, or creating ggplot2 puzzle visualizations.
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Create multi-stage Dockerfiles that separate build and runtime environments for minimal production images. Covers builder/runtime stage separation, artifact copying, scratch/distroless/alpine targets, and size comparison. Use when production images are too large, when build tools are included in the final image, when you need separate dev and prod images from one Dockerfile, or when deploying to constrained environments like edge or serverless.
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Parallel SDLC batch runner. Analyzes a list of independent task descriptions, groups them by heuristic file-conflict prediction, dispatches one worktree-isolated background agent per task (each running the full pipeline-orchestrator: BA → Dev → QA → Sec → Docs), and aggregates results into a single batch summary. Use when: - `/sdlc:batch` invokes this skill after parsing its arguments (Step 2 of commands/batch.md) - You have 2+ independent feature/fix descriptions to run through the SDLC pipeline in parallel Do NOT use for: - A single task (use pipeline-orchestrator directly via /sdlc:start) - Tasks that must share a single working tree (this skill isolates each task in its own git worktree)
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Framework-agnostic SQLAlchemy 2.0 core shared by fastapi-plugin and flask-plugin: declarative mapped classes with Mapped/mapped_column, column type selection, relationships with explicit lazy loading and cascades, 2.0-style select() querying, transaction/flush discipline, and Alembic-agnostic migration metadata rules. Framework plugins layer their delta skills (async sessions for FastAPI, Flask-SQLAlchemy integration for Flask) on top of this skill. Use this skill to: - Write SQLAlchemy 2.0 declarative models with Mapped[T] annotations and mapped_column(). - Pick correct column types (String(N), Numeric, DateTime(timezone=True), Uuid, Enum). - Define relationships with explicit lazy loading strategy and cascade settings. - Query with 2.0-style select() statements and manage flush vs commit boundaries. - Keep model metadata visible to Alembic autogenerate. Do NOT use this skill for: - FastAPI async engine/session lifecycle — see fastapi-plugin:sqlalchemy-patterns. - Flask-SQLAlchemy extension setup and Flask-Migrate — see flask-plugin:sqlalchemy-patterns. - Python idioms — see python-foundation:python-conventions.
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。
Next.js App Router routing primitives: file-based routes, dynamic and catch-all segments, route groups, parallel routes, intercepting routes, middleware, programmatic navigation, link patterns. Use this skill to: - Pick the correct dynamic segment syntax for the route shape. - Use route groups to organize without affecting URLs. - Implement parallel/intercepting routes for modal-style navigation. - Build effective middleware for auth, redirects, A/B tests. - Use Link and useRouter correctly. Do NOT use this skill for: - Data fetching per route (see nextjs-data-fetching). - General file conventions (see nextjs-conventions). - RSC vs Client (see server-component-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。
Angular Router (built-in `@angular/router`) — route configuration for standalone and NgModule projects, functional guards (Angular 14.1+), lazy loading, route resolvers, typed params via signals/observables, programmatic navigation, route data and meta. Use this skill to: - Configure routes (standalone-style or NgModule-style). - Use functional guards (canActivate as function, preferred over class-based in 17+). - Lazy-load components or feature modules. - Implement auth guards via route meta + functional guards. - Read params/queries via `inject(ActivatedRoute)` + signals or RxJS. Do NOT use this skill for: - General conventions (see angular-conventions). - State management (see angular-state-and-rx). - Forms (see angular-forms). - Testing routes (see angular-testing).
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Data fetching, caching, and revalidation patterns in Next.js App Router. Covers native fetch caching, ISR/SSG/SSR per-route choice, generateStaticParams, unstable_cache, revalidatePath/revalidateTag, Route Handlers, dynamic vs static rendering. Use this skill to: - Pick the right rendering mode (SSG / ISR / SSR / streaming) per route. - Use native fetch caching options correctly. - Build Route Handlers that match REST conventions. - Invalidate cached data after mutations. - Use generateStaticParams for dynamic SSG. Do NOT use this skill for: - RSC vs Client boundaries (see server-component-patterns). - Routing primitives (see nextjs-routing). - General conventions (see nextjs-conventions).
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。
Entity Framework Core patterns for ASP.NET Core projects: DbContext design, code-first entity configuration (Fluent API via IEntityTypeConfiguration<T>), relations (HasOne/HasMany, cascade/restrict/set-null), indexes and unique constraints, projection to DTOs (Select + AsNoTracking), avoiding N+1 (Include, AsSplitQuery), transactions, parameterized raw SQL (FromSql with FormattableString), and connection string from IConfiguration. Works alongside aspnet-core-plugin:aspnet-conventions. Use this skill to: - Design a clean DbContext with ApplyConfigurationsFromAssembly for scalable entity registration. - Configure entity properties (column types, max length, precision, nullability) via Fluent API. - Avoid N+1 query problems with explicit Include / projection to DTOs. - Use transactions correctly for multi-entity operations. - Write parameterized raw SQL safely when LINQ is not expressive enough. Do NOT use this skill for: - Migration generation commands (that is efcore-specialist's job in the database extra phase). - ASP.NET Core middleware, DI, or validation — see aspnet-core-plugin:aspnet-conventions. - C# language idioms — see csharp-foundation:csharp-conventions.
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。
pytest testing patterns for any Python project: test structure, fixtures, parametrize, conftest.py, monkeypatch, tmp_path, markers, unittest.mock (MagicMock, patch), pytest-cov coverage, and best practices. Stack-agnostic — referenced by every Python plugin in the marketplace. Use this skill to: - Organise tests with conftest.py shared fixtures and a clear test/src layout. - Write parametrized tests to cover multiple inputs without duplication. - Mock external dependencies (HTTP, DB, filesystem) with unittest.mock and monkeypatch. - Measure and enforce code coverage with pytest-cov. Do NOT use this skill for: - Framework-specific test types (Django TestCase / WebTestCase, FastAPI TestClient, Flask test client — see framework plugin skills). - Language idioms — see python-foundation:python-conventions.
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。
Fires after fixing any non-trivial bug or regression. Asks: could the graph have caught this as a guarantee? Pairs with reflection-in-and-on-action — picks up after "earliest catchable signal" and asks the next question: was that signal expressible in graph? Triggers: (1) after any non-trivial bug fix is verified working, (2) after a regression report (something used to work, broke), (3) during step 6 (knowledge extraction) of the workflow, (4) when reflection-on-action surfaces a "would have been catchable" signal. Outcome is a triage decision (graph-reachable? rule expressible? rule sound?) and either a draft Linear issue + guarantee proposal, or a recorded "graph capability gap" note. Never auto-creates guarantees.
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。
TanStack Router best practices for type-safe routing, file-based routing, data loading, search params, and navigation in React. Use when building React SPAs with complex routing, implementing type-safe search params, setting up route loaders, integrating with TanStack Query, or configuring code splitting and preloading.
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。
Type-safe URL query state management with nuqs 2.x. Use when writing or reviewing code that uses useQueryState, useQueryStates, URL search params, query parameters, nuqs parsers, createLoader, createSearchParamsCache, createSerializer, or URL state in Next.js, React, Remix, React Router, or TanStack Router.
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。
Director-level AI art prompt creation for Eastern beauty series, including Eastern fantasy / gu feng Chinese beauty character art, classical Eastern beauty, realistic and modern Eastern beauty, Cosplay展会摄影 / official convention cosplay photography with AAA game character campaign and Vogue editorial quality, 古风闺蜜 / AncientFemaleCompanionship two-person ancient Chinese female companionship photography, 东方美学图鉴 / 小红书图鉴 cover and content systems for 四大美人、四大才女、十二花神、东方神女、敦煌飞天、朝代服饰、东方器物、东方神话, 甜系纯欲生活写真 / SweetHomeGirl lifestyle portraits built around realism, feminine charm, romantic feeling, story moment, and natural attraction, new-Chinese-style fashion editorials, magazine portraits, worldbuilding, mythic role design, costume/styling systems, cinematic composition, lighting, negative prompts, and model-specific prompt variants. Use when the user asks for 东方美人, 东方审美, 东方美学图鉴, 小红书图鉴, 图鉴封面, 图鉴正文, 四大美人, 四大才女, 十二花神, 东方神女, 敦煌飞天, 朝代服饰, 东方器物, 东方神话, Cosplay展会摄影, coser, Coser, 漫展摄影, 展会摄影, ChinaJoy, Bilibili World, Tokyo Game Show, 游戏展台, 官方展会摄影, AAA游戏角色Cosplay, 古风闺蜜, AncientFemaleCompanionship, Ancient Female Companionship, 闺阁夜话, 姐妹古风写真, 古代闺阁生活, 灯下梳发, 共读, 夏夜纳凉, 守夜, 江南同行, 湖亭共伞, 山寺同行, 灯会夜游, 柔美, 妩媚, 成熟, 优雅, 高贵, 清冷, 温婉, 英气, 神性, 慵懒, 东方幻想, 古风美女, 古典东方美人, 宋韵, 唐宫, 江南, 洛神, 青瓷, 昆曲, 国风人物, 汉服女子, 写实东方美人, 现代东方审美, 新中式, 东方高级感, SweetHomeGirl, 甜系纯欲生活写真, 甜系纯欲, 甜美女友感, 真实女生, 自然抓拍, 故事感, 女友视角, lifestyle girlfriend portrait, 仙侠/武侠/宫廷/江南/敦煌风 AI 绘画提示词, image prompt optimization, style word expansion, character series concepts, or prompt packs for Midjourney, Stable Diffusion, ComfyUI, DALL-E, Gemini, Seedream, or other image generation tools.
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。
Shows you how to use Cowork's parallel workers to run multiple tasks at the same time instead of one after another — dramatically cutting the time on batch work. For processing large batches of files or research tasks, when running multiple independent analyses simultaneously, or during a performance optimization session. Use when the user says "speed up", "parallel workers", "batch task", "process multiple files", "why is cowork so slow", "faster", "do several things at once", or "can cowork multitask".
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 this skill when the user wants a Chinese adult-oriented turn-based text GalGame GM with harem formation, freeform narrative roleplay, natural-escalation yellow-fiction text adventure, multi-character relationship drama, story memory, or novel export. Trigger on requests for 后宫养成, 后宫, 养成, 多女主, 多男后宫, 黄色爽文, 自然流YY文字游戏, 成人向文字冒险, 回合制文字冒险, GalGame, 后宫互动, 逐步升温剧情, 暧昧开局, 自定义身份卡, 文档记忆, 小说导出, 女性向剧情, or any Chinese freeform narrative game where the user wants adult consenting characters, gradual escalation, strong character routes, and long-running continuity.
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 the user asks for a YARA rule, "write YARA for this sample/family", or `/hash-investigation` / `/malware-analysis` surfaces a sample worth a static-content rule. Pattern-matching rules for identifying malicious files.
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。
GraphQL and hidden parameter testing playbook. Use when exploring introspection, batching, undocumented fields, hidden parameters, schema abuse, and GraphQL authorization gaps.
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。