「arc」の検索結果

Improve search engine visibility with proper meta tags, structured data, sitemaps, and semantic HTML.

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。

Design and implement webhooks for event-driven architecture.

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 GLSL/WebGL/ShaderToy shaders and procedural visual effects such as SDF, ray marching, particles, and fluids.

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 synthesize a source-grounded multi-paper literature review. Use for systematic literature reviews, survey matrices, inclusion/exclusion criteria, research gaps, or "review the literature on X" requests; do not use for reviewing one paper, ordinary web summaries, citation formatting only, or medical/legal conclusions.

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。

Create, revise, or evaluate repository Agent Skills when the user asks to write a SKILL.md, improve triggers or information hierarchy, restructure references/scripts/assets, or diagnose skill predictability; do not use for product code, AGENTS.md initialization, general prompt editing, or automatic repository-wide cleanup.

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。

Resolve one exact official/current documentation gap when the user requests source verification or a version-sensitive API/SDK/provider/framework question can materially change the current decision; do not trigger for every implementation decision, ordinary framework code, local business logic, or broad research.

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。

Handle an explicit Git intent such as branch/worktree setup, commit organization, history archaeology, conflict resolution, PR preparation, or versioning; do not trigger as a process skill for every code or file 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。

Clarify a concrete requirements decision, create one bounded static interview packet, or run an explicitly user-invoked frontier batch over a plan, decision, or idea; trigger on explicit grill/interview/refinement intent or a named material ambiguity, not on ordinary planning, implementation, research, test-plan, report-style review, or BUILD work.

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。

Create or update source-grounded documentation when the user explicitly asks for docs/ADR/onboarding material, a public contract change requires docs, or an accepted hard-to-reverse decision meets the ADR gate; do not trigger for every feature, architecture discussion, implementation, review, or SHIP request.

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。

How to write modern Swift well — modeling with value types, Swift 6 data-race safety and approachable concurrency (@concurrent, main-actor-by-default, actors, task groups), protocols and generics (some vs any), API design, performance and ARC, Swift Testing, macros, and the modern language features agents don't know about yet. Use when writing, reviewing, or migrating Swift, or when a concurrency error, a hang, a data race, a retain cycle, or a performance problem needs fixing.

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。

Design, validate, and plan a startup from scratch. Covers market research, competitive analysis, business model, brand identity, product definition, financial projections, and validation experiments. Trigger when the user has a startup idea to explore, wants to validate a business concept, needs a business plan or lean canvas, asks for market sizing or competitive landscape, wants brand positioning or go-to-market strategy, or says anything like "I have an idea for..." or "is this idea worth pursuing". Also handles resuming from a previous checkpoint.

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。

Refactors route handlers into service layer with clean boundaries, dependency injection, testability, and separation of concerns. Provides service interfaces, folder structure, testing strategy, and migration plan. Use when refactoring "fat controllers", "business logic", "service layer", or "architecture cleanup".

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 Request for Comments documents for technical proposals including problem statement, solution design, alternatives, risks, and rollout plans. Use for "RFC", "technical proposals", "design docs", or "architecture proposals".

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。

Sets up monorepo architecture with Turborepo, pnpm workspaces, shared packages, and optimized build pipelines. Use when users request "monorepo setup", "Turborepo", "pnpm workspaces", "shared packages", or "multi-package repository".

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。

Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use improve-animations or review-animations instead.

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。

Converts documents into clean, chunked datasets suitable for embeddings and vector search. Produces chunked JSONL files with metadata, deduplication logic, and quality checks. Use when preparing "training data", "vector datasets", "document processing", or "embedding 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。

Token architecture, component specifications, and slide generation. Three-layer tokens (primitive→semantic→component), CSS variables, spacing/typography scales, component specs, strategic slide creation. Use for design tokens, systematic design, brand-compliant presentations.

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。

Elite mobile app image-generation skill for creating premium, app-native screen concepts and flows. Designed for iOS, Android, and cross-platform mobile products. Prioritizes clean hierarchy, comfortably readable text, strong multi-screen consistency, controlled color palettes, non-generic creative direction, textured surfaces, image-led composition, tasteful custom iconography, and clean phone mockup framing. By default, screens should be shown inside a subtle premium iPhone or similar phone mockup with a visible frame, while the main focus stays on the app content itself. This skill generates images only. It does not write 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。

Use when designing a Spark feature or writing or materially revising a design proposal that needs repository-first research, user input on unresolved key choices, and an owner-aligned implementation plan before code changes.

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 systematic, scoping, or rapid review needs a reproducible pipeline: protocol framing (PICO/SPIDER/PCC), a logged search string, title/abstract and full-text screening with recorded exclusion reasons, and PRISMA flow counts, with the human as the deciding screener.

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 complete research workflow — its instructions, skills, data boundaries, and tool connections — must be assessed for portability across AI agents or environments, so each component is explicitly mapped before migration rather than assumed to transfer.

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 research proposal needs work packages, milestones, deliverables, a timeline, a risk register, and budget-justification scaffolding, while keeping scientific claims and feasibility honest and human-owned.

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 for the search-planning stage of a literature review, when database lanes and language layers must be chosen, when DOI coverage policy is unclear, or when inclusion and exclusion criteria need drafting before any source is read; not for running the screening and PRISMA pipeline of a formal review, which is prisma-scoping-review-pipeline.

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 before a tag, GitHub release, or Zenodo archive, when README, CATALOG, CHANGELOG, CITATION.cff, the disclosure aggregate, and skill discovery must agree, or when a go or no-go release verdict needs recorded evidence behind it.

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。