「example」の検索結果

Write, rewrite, review, and organize developer-facing documentation for web software projects. Use when creating or improving README files, docs homepages, quickstarts, tutorials, how-to guides, API/reference pages, conceptual explanations, migration guides, or troubleshooting content for frontend, backend, full-stack, SDK, API, or framework-based web products. This skill applies strong information architecture, task-first page structure, clear voice, runnable examples, version and prerequisite hygiene, accessibility rules, and docs-as-code maintenance habits. Do not use it for marketing copy, legal text, or non-technical customer-support articles.

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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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。

Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.

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 up-to-date library and framework docs via Context7 MCP instead of training data. Activates for setup questions, API references, code examples, or when the user names a framework (e.g. React, Next.js, Prisma).

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 articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.

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。

Audits env var config: file inventory, code-to-example sync, default desync, naming, startup validation. Stack-adaptive.

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 file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for relational database workloads.

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 update GitHub PR titles and PR bodies with repository templates and local conventions. Use when creating PRs with `gh pr create`, revising PR text, choosing a conventional title prefix (for example `feat(web):`), or ensuring ticket suffix rules.

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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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 nostalgic, vintage-inspired cityscape with a muted, sepia-toned color palette.

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 fantasy landscape with a vibrant, sunset-inspired color palette of orange, pink, and purple.

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 or update dygo instructions, reference documentation, task descriptions, CLI help, metadata examples, or architecture notes. Use when documentation quality and contract accuracy are central to the task.

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 debug spreadsheet formulas (Excel/Google Sheets), pivot tables, and array formulas; translate between dialects; use when users need working formulas with examples and edge-case checks.

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 authoring Litestar skill content, Python/TypeScript examples, PEP 604, async I/O, Google docstrings, ruff/mypy/pyright, pytest, or CI rules. Not for focused Litestar APIs.

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。

Look up word definitions, pronunciations, parts of speech, and usage examples from the Free Dictionary 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。

Loads, lists, composes, or validates graded evaluation rubrics: PASS/WARN/FAIL grading with weighted criteria and balanced anchor examples for evaluator-style 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。

Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".

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。

Comprehensive reference for inter-process communication mechanisms -- every way processes can talk on a computer. Covers sockets (TCP, UDP, Unix domain), WebSockets, SSE, pipes (named/anonymous), shared memory (mmap, shm_open), message queues, signals, D-Bus, XPC (macOS), gRPC, REST, stdin/stdout, file-based coordination, and clipboard. Performance benchmarks, platform availability, and code examples for each. Special focus on which IPC works best for AI agent coordination. Activate on: "IPC", "inter-process communication", "process communication", "how do I talk between processes", "Unix socket vs TCP", "shared memory", "named pipe", "WebSocket vs SSE", "gRPC vs REST", "agent coordination IPC", "XPC service", "message passing", "stdout pipe", "D-Bus", "mmap". NOT for: distributed systems design (use distributed-systems), network protocol design (use networking), message queue infrastructure like Kafka (use data-pipeline-engineer).

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。

Metal/wgpu/WGSL shader surfaces for native Rust gpui apps (Zed-family, pd-console), stockpiled with beautiful copy-pasteable shader-toy examples. Use for custom GPU fragment passes behind/around gpui panes: ocean/water shaders, pixelated waves and boats, a living harbor, dithered chrome borders, sonar sweeps, aurora/starfields, CRT/scanline post. Trigger on: wgsl, wgpu, metal shader, gpui shader, shadertoy, fragment shader, SDF, noise/fbm, ordered dithering, pixelation, render-to-texture, "pixelated waves and boats", living harbor water. NOT for: web/GLSL/three.js shaders (use a web tool), non-shader gpui motion (use rust-gpui-motion), general GUI layout/color (use beautiful-gui-design), CLI/TUI (use beautiful-cli-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。

Generates production-ready design tokens from natural language descriptions. Outputs Tailwind configs, CSS custom properties, and DTCG W3C tokens from 24 trends + 31 AI-ready styles with 2800+ component examples.

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。

Creates comprehensive documentation for design systems - token tables, usage guidelines, component examples, and accessibility notes. Use after generating tokens to create developer-friendly docs.

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。

What you can build and do with an always-on AI agent that has episodic memory. Covers concrete product ideas, workflows, emergent capabilities from persistence plus memory, and real-world examples of deployed persistent agents. Helps you go from "I have the architecture" to "here's what it actually does for me." Activate on: "what can an always-on agent do", "persistent agent use cases", "agent applications", "proactive agent ideas", "what to build with episodic memory", "always-on agent product", "personal AI assistant ideas", "/always-on-agent-applications". NOT for: building the architecture (use always-on-agent-architecture), designing inputs (use always-on-agent-inputs), safety and privacy (use always-on-agent-safety).

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。

Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the gene-independent DNA-damage / G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.

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。