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概要と使いどころ
Create or redesign appointment-based service websites for salons, barbers, spas, wellness studios, clinics, and hospitality brands. Use for warm editorial layouts, serif-led identity, documentary portrait crops, calm treatment selectors, location-aware booking, and operational states that remain elegant and trustworthy.
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。
Draws flat vector spot illustrations of tall, long-legged people doing design and coding things, with solid black as a main colour. Traits: no outlines on coloured fills; black as big solid shapes (hair, trousers, shoes, devices) and as thin detail lines; denim blue, leaf green, sun yellow and tomato red on cream skin; dot eyes, round glasses and blush; big shoes on one thin black ground line; two stars and two plus-sparkles as the only decor. Covers palette, line weights, characters, heads, hands, props, composition and a parts helper for limbs, shoes, heads, hands and paper props. Use when someone asks for flat illustration with black, flat people or character illustration, friendly product or SaaS illustration, or art for empty states, onboarding, 404 and error pages, blog headers, feature spots, marketing cards or app screens in this style.
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 truthful Vesperfall asset-library review pairs from transparent PNG references and live Three.js, FBX, or img2threejs models. Use when adding a character, enemy, prop, or equipment asset to the Vesperfall catalog; creating a card-PNG plus inspector-model treatment; exposing an isolated model or moveset route; or standardizing provenance, grounding, tests, and Codex-browser validation for game art 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。
Create, integrate, or audit production-ready rigged 3D characters and monsters with a main model, skeleton, animation library, sockets, collision contracts, separate character equipment, optimized runtime files, catalog media, and an interactive moveset inspector. Use when generating or importing FBX/GLB game actors; defining character-versus-monster asset requirements; separating swords, shields, helmets, armor, or stowed gear; adding idle, walk, run, attack, hit, dodge, block, cast, or death clips; wiring an asset into gameplay; or adding action and equipment controls plus deterministic tests to a game asset catalog.
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。
TypeScript library for NEAR Protocol blockchain interaction. Use this skill when writing code that interacts with NEAR Protocol, including viewing contract data, calling contract methods, sending NEAR tokens, building transactions, creating type-safe contract wrappers, integrating wallets (Wallet Selector, HOT Connect), React hooks and providers (@near-kit/react), managing keys, testing with sandbox, meta-transactions (NEP-366), and message signing (NEP-413).
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。
Internet Court adapter for GenLayer Intelligent Contract supervision. Use to specify agent-performance rubrics, evidence schemas, decision outputs, and ERC-7710 connector expectations, while delegating actual GenLayer contract writing, linting, testing, deployment, and CLI interaction to the official GenLayer skills at https://skills.genlayer.com/.
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。
Entry point for Internet Court — the trust layer for agent-to-agent commerce. Use whenever an agent needs to transact with another agent or a paid service, or a user mentions agent payments, paid APIs (HTTP 402/x402), wallet custody or trust concerns, spending mandates, delegated permissions (ERC-7710/7715), escrow, agent identity or reputation (ERC-8004), negotiation between agents (A2A), agent jobs (ERC-8183), machine payments (MPP, AP2), supervision of agent behavior, revocation, verification, or dispute resolution (GenLayer) — even if they never say "Internet Court". Routes to the vendored protocol skills and connector skills in this package.
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。
Connect GenLayer Intelligent Contract decisions to ERC-7710-style delegated authority. Use when an agent needs to design the interface, message schema, relayer/bridge path, EVM revocation controller, constraint updates, proof/finality assumptions, and failure handling that turn a GenLayer agent-performance review into ERC-7710 revocation or policy 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。
Design n8n AI agents the right way. Use when building or editing any @n8n/n8n-nodes-langchain.* AI node — an AI Agent, LLM chain, Text Classifier, or Information Extractor — and whenever the user mentions AI agents, LLM with tools, tool calling, $fromAI, system prompts, agent memory, sessionId, structured/JSON output, output parser, RAG, vector store, a chat assistant/bot, or human-in-the-loop review. Covers Agent-vs-chain-vs-classifier choice, the model/memory/tools/outputParser slots, tool names/descriptions as prompt, structured output with autoFix, memory, RAG, human review, and chat topologies.
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。
Diagnose demonstrated CPU, command latency, allocation or IO regressions in an owned process with controlled measurements and language-appropriate profilers. Route benchmark effectiveness, score growth and trajectory efficiency to loopx-benchmark; profiling does not qualify a budget or grant execution authority.
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。
Operate or analyze LoopX-managed benchmark experiments through benchmark-toolkit, including trajectory-based effectiveness and efficiency diagnosis, matched comparisons, run selection and integrity. Solving an assigned task under an existing runner does not by itself select this skill. Excludes casual benchmark discussion and ordinary software microbenchmarks.
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 developing LLM agents based on PuerTsAgent framework — covers resource directory structure, system-prompt, skills, builtin modules, and best practices.
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。
Scrapes tweets from X (Twitter) by search query, user handle, or direct URL — returns full tweet data including text, author info, engagement metrics, media, and hashtags. Use when user mentions X, Twitter, tweet scraping, scrape tweets, get tweets, fetch tweets, twitter data, x.com data, tweet collector, tweet search, twitter search, social media scraping, twitter handle scraping, scrape user tweets, from:username, twitter keyword search, hashtag search, twitter timeline, twitter list scraping, collect twitter posts, export tweets, tweet analysis, twitter monitoring, search twitter, get twitter data, twitter api alternative, tweet dump.
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 Xiaohongshu (RedNote / xhs) notes by keyword and return a paginated list with title, author, engagement stats (likes, collects, comments), cover image URL, and xsecToken for detail lookup. Use when user mentions find notes on xiaohongshu, search rednote, search xhs, scrape xiaohongshu search, xiaohongshu keyword search, rednote post search, xhs search results, monitor xiaohongshu topics, KOL content discovery via xiaohongshu, xiaohongshu note list, rednote scrape, xhs data collection, collect xiaohongshu posts, xiaohongshu topic search, xiaohongshu content monitoring, rednote post list, xhs keyword scrape.
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。
Walmart product reviews scraper: given a walmart.com product item ID, navigate to the reviews page and extract paginated customer reviews including reviewId, rating, title, review text, author nickname, submission date, verified purchase status, helpful votes, variant selected (color/size), badges, fulfilled by, seller name, and photo count. Use when user mentions walmart reviews, walmart product reviews, walmart customer reviews, scrape walmart reviews, extract walmart reviews, walmart review scraper, walmart ratings and reviews, walmart review data, walmart review text, walmart review pagination, get reviews from walmart, walmart review collector, walmart verified purchase reviews, walmart review analysis, walmart sentiment analysis, walmart review export, walmart buyer feedback. Also applies to bulk collection of walmart product reviews across multiple items, sentiment analysis on walmart reviews for market research, competitor product review benchmarking on walmart, and monitoring new walmart reviews over time.
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。
Automatically check code changes since last tag and update documentation in docs/ directory (en, zh-CN, ja-JP) and CLAUDE.md to ensure consistency with actual code implementation
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。
Manage Git worktrees in project-level ../.zcf/project-name/ directory with smart defaults, IDE integration and content migration
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。
AI(ChatGPT·Claude·Gemini 등)가 쓴 한글 텍스트를 "사람이 쓴 글처럼" 윤문해주는 오케스트레이터 스킬. 번역투·영어 인용 과다·기계적 병렬·관용구·피동태 남용·접속사 남발·리듬 균일성·이모지/불릿 과다 등 10대 카테고리 85개 AI 티 패턴을 탐지·분류해 내용은 한 글자도 건드리지 않고 문체·리듬·표현만 자연스러운 한국어로 재작성한다. shim의 route_hint(light|standard|heavy)로 경로를 정해 잘 쓴 글은 1콜, 표준은 2콜, 중증·장문만 3+콜(진단→겨냥 윤문→finalize)로 처리한다. 트리거 — "AI 티 없애줘", "AI 같은 글 자연스럽게", "GPT/ChatGPT 문체", "AI 번역투 고쳐", "사람이 쓴 것처럼 윤문", "AI 윤문", "ChatGPT 티 제거", "한글 AI 탐지·윤문", "AI 글 사람처럼", "번역투 제거", "영어 인용 많은 글 윤문", "AI 글 티 안 나게", "휴머나이저", "humanize Korean", "AI detector bypass 한글". 후속 작업 — "특정 카테고리만 다시", "윤문 강도 조정", "장르 바꿔서", "이 문단만", "2차 윤문" 도 모두 이 스킬. 단순 맞춤법·오탈자 교정은 직접 처리, 번역은 번역 스킬, 내용 추가·삭제를 동반한 재작성은 별도 집필 스킬.
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 a plugin", "scaffold a plugin", "understand plugin structure", "organize plugin components", "set up plugin.json", "use ${CLAUDE_PLUGIN_ROOT}", "add commands/agents/skills/hooks", "configure auto-discovery", or needs guidance on plugin directory layout, manifest configuration, component organization, file naming conventions, or Claude Code plugin architecture best practices.
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。
Coordinate access to shared task directories using .processing marker files. Use before accessing a Worker's workspace to prevent conflicts when both Manager and Worker might modify files simultaneously.
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 any Leader taskflow call or task-level workflow involving delegating a ready DAG or Loop node, writing task meta/spec, checking a Worker task result, handling result statuses, task directory ownership, or Worker result contracts. Always use this skill when the request mentions delegate_task, check_task, task result.md, task spec.md, BLOCKED, REVISION_NEEDED, INTERRUPTED, SUCCESS, or assigning/delegating a Worker 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。
Build continuous-shot motion-driven HTML stories from a subject or narrative, including research, story structure, consistent AI stills, Seedance scene and connector clips, interface styling, media normalization, and browser QA. Use for immersive journeys, timelines, product stories, fictional worlds, or other scene-based visual narratives whose camera should flow from beginning to end; not for ordinary autoplay video pages or general web apps.
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。
Scaffolds new agent skills for the dotnet/skills repository. Use when creating a new skill, generating SKILL.md files, writing a skill description that the runtime will actually route to, or setting up skill directory structures. Handles frontmatter generation, section templates, and validation guidance. Do not use for fixing a skill that already fails its evaluation (use improve-skill-quality) or for writing eval.yaml (use create-skill-test).
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 .NET projects from templates with validated parameters, smart defaults, Central Package Management adaptation, and latest NuGet version resolution. USE FOR: creating new dotnet projects, scaffolding solutions with multiple projects, installing or uninstalling template packages, creating projects that respect Directory.Packages.props (CPM), composing multi-project solutions (API + tests + library), getting latest NuGet package versions in newly created projects. DO NOT USE FOR: finding templates (use template-discovery), producing a detailed side-by-side comparison of templates (use template-comparison), authoring custom templates (use template-authoring), deciding cross-parameter defaults such as which framework to pair with native AOT or whether to keep HTTPS when auth is enabled (use template-smart-defaults), modifying existing projects or adding NuGet packages to existing projects.
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。