「used」の検索結果

A luxury-automotive brand whose marketing surfaces read as cinematic editorial. The base canvas is **near-black** (`#181818`) holding pure white display type; white-canvas bands appear only inside specific editorial contexts (preowned listings, pricing tables). The single brand voltage is **Rosso Corsa** (`#da291c`) — the iconic Ferrari racing red — used scarcely on primary CTAs, the Cavallino mark, and Formula 1 race-position highlights. Type runs **FerrariSans** at modest weights (display 500, body 400) — never bombastic. Spacing follows an explicit 8px token ladder (`xxxs` 4px through `super` 128px); generous editorial pacing throughout. The brand's strongest visual signature is the **full-bleed cinematic hero photograph** that fills the viewport top with car photography, model details, or trackside livery — followed by a tighter editorial body layout below.

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 terminal-native marketing system rendered entirely in Berkeley Mono — every word on the page, from the hero headline down to the footer fine print, is monospaced. The page itself reads like a manpage or a static-site README: warm cream canvas (`#fdfcfc`), nearly-black ink (`#201d1d`), 4px-radius rectangles for the few interactive elements, and bracketed `[+]`/`[-]` ASCII markers used as bullets. The brand's only "visual moment" is a single dark hero card that mocks up the OpenCode TUI itself — black background, monospaced terminal output, ASCII pipe characters, and a wordmark rendered as block-pixel ASCII. Every section sits as a hairline-bordered text block on the cream canvas with no shadows, no gradients, no decorative imagery, and no non-monospaced character anywhere in the system.

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 creating or rewriting README.md for projects. Triggers on "write README", "create README", "update README". Creates human-focused documentation with proper structure.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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 "set up Nuxt Studio", "configure Studio OAuth", "deploy Studio to Cloudflare", "add visual editor to Nuxt", "configure studio.domain.com subdomain", "Studio authentication", "Nuxt CMS", or mentions visual content editing, Nuxt Studio module, TipTap editor, Monaco editor, or content management for Nuxt websites.

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 "set up Cloudflare Queues", "create a message queue", "implement queue consumer", "process background jobs", "configure queue retry logic", "publish messages to queue", "implement dead letter queue", or encountering "queue timeout", "message retry", "throughput exceeded", "queue backlog" errors.

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 "upload images to Cloudflare", "implement direct creator upload", "configure image transformations", "optimize WebP/AVIF", "create image variants", "generate signed URLs", "add image watermarks", "integrate with Next.js/Remix", "configure webhooks", "debug CORS errors", "troubleshoot error 5408/9401-9413", or "build responsive images with Cloudflare Images API".

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。

Cloudflare Hyperdrive for Workers-to-database connections with pooling and caching. Use for PostgreSQL/MySQL, Drizzle/Prisma, or encountering pool errors, TLS issues, connection refused.

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 "add turnstile", "implement bot protection", "validate turnstile token", "fix turnstile error", "setup captcha alternative", or encounters error codes 100*/300*/600*, CSP errors, or token validation failures. Provides CAPTCHA-alternative protection for Cloudflare Workers, React, Next.js, and Hono.

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 "bun:ffi", "foreign function interface", "calling C from Bun", "native libraries", "dlopen", "shared libraries", "calling native code", or integrating C/C++ libraries with Bun.

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 "Cloudflare Workers with Bun", "deploying Bun to Workers", "wrangler with Bun", "edge deployment", "Bun to Cloudflare", or building and deploying applications to Cloudflare Workers using Bun.

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 "Next.js with Bun", "Bun and Next", "running Next.js on Bun", "Next.js development with Bun", "create-next-app with Bun", or building Next.js applications using Bun as the runtime.

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 "bun build", "Bun.build", "bundling with Bun", "code splitting", "tree shaking", "minification", "sourcemaps", "bundle optimization", "esbuild alternative", "building for production", "bundling TypeScript", "bundling for browser", "bundling for Node", or JavaScript/TypeScript bundling with Bun.

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 "WebSocket in Bun", "real-time communication", "Bun.serve websocket", "ws server", "socket connections", "pub/sub", "broadcasting messages", "WebSocket upgrade", or building real-time applications with Bun.

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。

Inspect an unfamiliar repository, turn a focused Markdown behavior scenario into a deterministic test in the repository's native test stack, run it, and preserve traceability between intent and code. Use when asked to add scenario tests, compile acceptance criteria or Given/When/Then Markdown into executable tests, reproduce a user-visible regression, or convert a narrow workflow specification into stable web, API, CLI, desktop, or mobile interaction coverage. Do not use for broad exploratory journeys or agent-judged smoke tests.

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。

Threat-model and harden AI agents, RAG systems, assistants, and tool-using workflows against direct, indirect, stored, cross-agent, and multimodal prompt injection. Use when reviewing an agent architecture, isolating untrusted content, constraining tools and egress, protecting secrets, adding injection-focused tests, investigating a suspected injection incident, or documenting residual prompt-injection risk.

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 creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

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。

Think and work like an expert Bioinformatics Engineer. Use when a task calls for Bioinformatics Engineer judgment. Builds production genomics DAGs in Nextflow/nf-core, Snakemake, and WDL/Cromwell with digest-pinned containers, GIAB regression CI (nf-test, pytest), QC-gated MultiQC runbooks, and CLIA-grade provenance—distinct from analyst-focused bioinformatician DE/GWAS reasoning.

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。

Scaffold and amend the L1 Investment Constitution — [ALL_CAPS] placeholder bootstrap, SemVer bump rules, Sync Impact Report, MINOR/MAJOR re-examination dispatch after the gate-5 budget confirm. Thesis creation stays refused until ratification (Q83).

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。

Testing workflow skill for finding high-value test candidates, writing focused tests, generating realistic workloads, reviewing test value, and diagnosing test-suite health. Use for prompts about what to test next, adding or improving tests, reviewing whether a test is worth keeping, low-signal or flaky tests, workload scenarios, or test-suite trust. Do not use for general QA discussion unless the user wants a concrete testing workflow or artifact.

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。

Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment.

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。

Produce, direct, integrate, and quality-control ElevenLabs text-to-speech for narration, character performance, multilingual media, long-form voiceover, and streamed or batch AI-content audio. Use when selecting ElevenLabs models or voices; preparing spoken text; controlling pronunciation, pacing, emotion, and code-switching; using TTS APIs; cloning or designing a voice with consent; repairing artifacts; mastering deliverables; or evaluating generated speech. Excludes music, sound-effect generation, conversational-agent design, and general speech recognition except transcription used to verify TTS.

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 discussions, track communities, analyze posts, and discover trends on Reddit through SandBase. Use when asked for Reddit research, community analysis, trending topics, discussion monitoring, content discovery, or audience insight beyond customer-focused 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。

Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.

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。