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概要と使いどころ
Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authenticat...
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。
Generate AI videos with Google Veo, Seedance, Wan, Grok and 40+ models via inference.sh CLI. Models: Veo 3.1, Veo 3, Seedance 1.5 Pro, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Capabilities: text-to-video, image-to-video, lipsync, avatar animation, video upscaling, fole...
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 to "create AGENTS.md", "update AGENTS.md", "maintain agent docs", "set up CLAUDE.md", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.
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。
Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, confidence scoring, and command validation.
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 multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, market...
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 a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
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 working with VueUse composables - provides reactive utilities for state, browser APIs, sensors, network, animations. Check VueUse before writing custom composables - most patterns already implemented.
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。
Redesign GitHub README homepages or create project-native pure SVG, hybrid SVG-composed PNG/WebP, and opt-in animated GIF assets. Use when a user asks to beautify, redesign, rebrand, visually upgrade, simplify, or audit a GitHub README; create only a hero, section headers, diagrams, badges, motion graphics, showcase modules, or other README assets; or turn a repository homepage into a cohesive visual story. If whole-README work versus asset-only work is unclear, ask which scope the user wants. For hero-like assets where pure SVG and generated raster material are both viable, explain the tradeoffs and confirm the implementation before creating the asset.
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。
Coach German writing and conversation with minimal corrections, persistent root-cause mistake tracking (FehlerDNA), mistake-based spaced repetition with a new sentence every time, roleplay whose words return in spaced reviews, continuing preparation for real-life goals across sessions, and an honest progress profile. Use for German correction, personalized review, vocabulary, progress, roleplay, or preparation for an interview, presentation, appointment, or other concrete event; do not use for translation-only requests without learning or feedback.
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 developing code using Test-Driven Development (TDD) methodology. Use this skill when the user wants to write tests first before implementation, needs guidance on the red-green-refactor cycle, or explicitly requests TDD-style development. Triggers include requests like "develop this feature using TDD", "write tests first", "help me with test-driven development", or "implement this following TDD practices". The skill guides through writing failing tests, implementing minimal code to pass, and refactoring while maintaining test coverage.
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 about "Hyprland configuration", "hyprland.lua", "hyprland.conf", "Hyprland Lua config", "hyprctl", "Hyprland keybinds", "Hyprland window rules", "Hyprland monitors", "Hyprland dispatchers", "Hyprland animations", "Hyprland workspaces", "Hyprland IPC", "Hyprland plugins", "hyprlock", "hypridle", "hyprpaper", "hyprcursor", "hyprpicker", "hyprsunset", "xdg-desktop-portal-hyprland", "Hyprland on NixOS", "Hyprland Home Manager", "Hyprland layouts", "Hyprland dwindle", "Hyprland master layout", "Hyprland FAQ", "Hyprland performance", "Hyprland Nvidia", "Hyprland screen sharing", "Hyprland special workspace", "Hyprland smart gaps", "Hyprland multi-monitor", "Hyprland tearing", or any topic related to configuring, troubleshooting, or extending the Hyprland Wayland compositor and its ecosystem 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。
Use when the user uploads a screenshot of a hero section or landing page (or a URL/description of one) and wants a copy-paste-ready developer prompt to recreate it exactly in a tool like Lovable, Bolt, Replit, or Cursor. Produces prompts with exact hex colors, Tailwind classes, animation timing tuples, and component structure — not vague descriptions.
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。
Audit a dataset or access rule before it joins an identity-graph build (access rules behave like datasets in NQL here). Enumerates failure modes (hub identifiers, high-degree nodes, suspicious values, over-connected identifiers), tests hypotheses in parallel, quantifies damage by rows / edges / entities, and proposes minimal filters ranked by severity. When issues are found, returns a validated `CREATE MATERIALIZED VIEW` NQL the caller can run to produce a graph-ready clean source; if the data passes, says so and recommends it unchanged. Plans and authors the clean-view NQL; does not execute it. Use when: "audit this dataset before the graph build", "find bad edges in <source>", "check identity data quality", "recommend filters for the graph build", "quantify damage from <identifier_type>", "pre-graph DQ". (narrative-identity)
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。
ディズニーの12原則とジブリ的自然運動をベースに、UIアニメーションの「なぜ動かすか」「どう動かすか」を判断する。アニメーション/モーション/トランジション設計の相談で、ツール非依存の概念的判断軸として使う。
Write p5.js prototypes into the lab — sketches that actually run in a browser, seed-reproducible, with controls generated from the sketch's own parameters. Use for generative art, flow fields, particle systems, noise, animation, anything sketched visually in the browser.
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。
Heuristic-first software surgery for proof-backed, minimal-diff implementation: Contract to Invariants to Cut Rationale to inevitable incision to Proof. Use when users say "run /tw-tk", "patch-first", "keep the diff small", "state contract + invariants", "one clear incision", "fix it with a validation signal", or orchestration cues like "workers use /tw-tk" / "internally use /tw-tk".
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。
Refine an existing skill in place with minimal diffs. Trigger when asked to improve a skill's trigger description/frontmatter, workflow text, metadata, scripts/references/assets; also for requests to iterate, refactor, rename, or fix a skill using usage/session-mining evidence (for example from /tw-seq).
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。
Compress review pressure into the right next action instead of more code by default. Classify findings, reject non-liabilities, and choose proof-only vs minimal-fix vs refactor-kernel, preventing one-patch-per-comment churn. Use after a code review — PR comments, reviewer suggestions, or audit findings — and especially when you are about to reflexively patch every comment.
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。
Set up and manage a UI redesign experiment with three git worktree branches for modern minimal, bold creative, and classic refined design directions. Use when asked to run a UI redesign experiment, compare design approaches, or prototype multiple visual directions in parallel branches.
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 Steven's Bash script style rules: strict mode, minimal validation, concise logic, executable scripts, and no unnecessary comments or echoes. Use when creating, reviewing, or refactoring shell scripts.
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 implementing a new function, adding a feature, fixing a bug, refactoring with test coverage, or writing a new test. Enforces strict outside-in red-green-refactor TDD with one-failure-per-turn discipline, predict-the-failure-before-every-run checks, hardcode-first minimum changes, triangulation, and property-based testing for large input spaces. Triggers on explicit TDD requests and on any task phrased as "implement", "add", "write a function", "build a feature", or "fix a bug" in a test-capable codebase. Reports red/green validation evidence.
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 a local codebase and infer the architecture it is actually using, including repo kind, best-fit dominant architecture, directly evidenced coexisting patterns, major subsystem exceptions, confidence, docs-vs-code drift, and repo-fit hints for downstream agents. Use when prompts ask what architecture a repo uses, whether it is really hexagonal or just layered, what subtle patterns shape a repo or slice, how a target slice fits a hybrid monorepo, whether documented architecture matches implementation, or when `/tw-tk` needs a repo-dialect preflight before making a minimal change.
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。
Review+fix protocol with optional pre-core git diff review and safety guardrails (unsoundness, invariants, footguns, incidental complexity). Use when prompts say "/tw-fix this PR", "fix current branch", "fix this diff", "repair CI red", or "apply a minimal patch", and when crash/corruption/invariant-break issues need correction with a validation signal. Stop only after self-review exhausts actionable changes, each full cycle reaches post-self-review rerun plus terminal diff-review closure, and two consecutive zero-edit full cycles are clean.
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。
Compile deep repository evidence into artifact-bound correctness doctrine — authority/law/proof maps, owned invariants, failure archaeology, and the strongest durable destination for each piece of knowledge, plus an optional minimal repository-specific skill portfolio. Use when the user wants both deep codebase understanding AND durable doctrine, knowledge routing, or repo-specific skill recommendations. Research discoverable facts before asking. Read-only. Not for quick onboarding, one isolated invariant, ordinary implementation, generic review, or direct skill creation.
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。