7,424 件 ・ 関連度順
概要と使いどころ
Discover and filter URLs on a known website through Tavily without extracting every page. Use to locate a specific subpage, inspect site structure, or prepare a bounded map-then-extract workflow.
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 doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).
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 and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
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。
Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
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。
Expert en technologies de soin aux personnes âgées avancées (fall detection, medication reminders, social connection, accessibility)
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。
Cloud Engineer IA — Expert en infrastructure cloud (AWS, GCP, Azure, Terraform, K8s, serverless). Conçoit et déploie des architectures cloud natives.
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 NVIDIA App's local MCP tools for application, driver, game-optimization, laptop-feature, and restricted In-Game Overlay operations and troubleshooting.
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。
PRコードレビュー。複数の観点（ロジック・セキュリティ・パフォーマンス・設計整合性）で 並列レビューし、統合結果を出力する。 「PRをレビューして」「このPRの問題点を見て」「PR#123を確認して」 「コードレビューして」などのリクエストで使用する。 PR番号・URL指定、またはカレントブランチのPRを自動検出する。
ローカルのExcelファイル（MemberList）をJSON形式に変換する
Convert any landing page or website into an Ozor.ai video prompt. Use this skill whenever the user provides a URL, landing page content, or website copy and wants to turn it into a video. Trigger on phrases like 'make a video from my website', 'video from this landing page', 'turn my homepage into a video', 'video from this URL', 'product page to video', 'website to video', 'marketing video from my site', 'convert this page to video', or any request to transform web content into video format using Ozor.
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。
Turn a real document (PDF, PPTX, DOCX, Keynote export, slide deck, proposal, whitepaper, report) into a finished AI-generated video using the Ozor MCP. Use this skill whenever the user attaches, uploads, references, or points to a document file and wants a video from it — e.g. 'make a video from this pitch deck', 'turn this PDF into a video', 'video from my proposal.docx', 'generate a video from this PowerPoint', 'create a video from this report', 'this whitepaper → video'. This skill runs the document-to-video pipeline: analyze_document → present the plan to the user → update_plan if needed → generate_from_plan → export_video → wait_for_export → get_embed_code. It always uses the plan-based flow so slide visuals are preserved. Do NOT use this skill for plain-text creative briefs (use ozor-generate) or for URLs/landing pages (use ozor-url-to-video).
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 SwiftUI layouts using stacks, grids, lists, scroll views, forms, and controls. Covers VStack/HStack/ZStack, LazyVGrid/LazyHGrid, List with sections and swipe actions, ScrollView with ScrollViewReader, Form with validation, Toggle/Picker/Slider, .searchable, and overlay patterns. Use when building data-driven layouts, collection views, settings screens, search interfaces, or transient overlay UI.
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 iOS App Clips with invocation URLs, NFC, QR codes, App Clip Codes, Safari banners, Maps, Messages, and shared App Group data handoff to the full app. Covers target setup, experience configuration, size limits, NSUserActivity handling, SKOverlay promotion, location confirmation, and capability limits. Use when creating App Clips or wiring App Clip invocation and full-app 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。
Manual testing + bug filing for Enterprise / SaaS products. Parses a Feishu test doc (scope + repo + bitable URL), observes staging via claude-in-chrome, captures DOM/console/network/screenshot evidence, then dual-tracks each finding — Feishu Bitable record (with attachments) + GitHub issue (<REPO>#<ISSUE_NUMBER> format — English-primary, Chinese collapsed, R2-hosted screenshots, matching type label). Enforces dedup across bitable + GitHub issues + PRs, and mandatory P0/P1/P2 priority prompt when unclear. Trigger whenever the user says "test and report", "test and report side-by-side", "start system testing", "experience staging", "collaborate on bug filing", "collect feedback", a shared Feishu testing doc, a bitable URL + finding, or any UX/bug needing both bitable + GitHub tracking. Do NOT use for writing product code, PR review, CI debugging, or general "how do I use this product" questions — those go to normal dev / PR-review / support flows.
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。
从小说/策划案原文与故事大纲中抽取并组织结构化世界设定，按"子类型分组的统一卡片"JSON 模板写入 /project/world.json。当需要生成或修订世界设定时使用。
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 dataset construction — SupervisedDatasetBuilder, RLDatasetBuilder, ChatDatasetBuilder, and custom dataset creation from JSONL, HuggingFace, or conversation data. Use when the user asks about datasets, data loading, data preparation, or custom data formats.
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。
When the user wants to create or optimize popups, modals, overlays, slide-ins, or banners for conversion purposes. Also use when the user mentions "exit intent," "popup conversions," "modal optimization," "lead capture popup," "email popup," "announcement banner," or "overlay." For forms outside of popups, see form-cro. For general page conversion optimization, see page-cro.
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。
Inngest expert for serverless-first background jobs, event-driven workflows, and durable execution without managing queues or workers. Use when: inngest, serverless background job, event-driven workflow, step function, durable execution.
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。
Expert at handling file uploads and cloud storage. Covers S3, Cloudflare R2, presigned URLs, multipart uploads, and image optimization. Knows how to handle large files without blocking. Use when: file upload, S3, R2, presigned URL, multipart.
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。
Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.
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。
Deploy web apps with backend APIs, database, and file storage. Use when the user asks to deploy or publish a website or web app and wants a public URL. Uses HTTP API via curl.
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。
X/Twitter via xurl CLI: post, search, DM, media, v2 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。
Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape. Activate on "find expungement data", "scrape state laws", "legal research", "court URLs", "statute sources", "Clean Slate laws", "automatic expungement research". NOT for interpreting laws (use national-expungement-expert), building UI, or legal advice.
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。
Vendor (copy-import) a single external Claude Code skill into your own skills repo correctly — with license compliance and full provenance/attribution. Deterministic, idempotent primitive: given an upstream ref (owner/repo/path@sha or a GitHub URL) it fetches the skill, detects and gates on the license, copies the folder, injects a provenance frontmatter block (license + metadata: author/source/upstream_commit/vendored_at/provenance), ships the upstream LICENSE, adds a ## Credits section, and records a CREDITS.md ledger entry. Use when the user asks to "vendor a skill", "import a skill", "clone a skill", "borrow someone's skill", "add an external skill with attribution/credit", or スキルを取り込む / vendoring / 他人のスキルを自分のリポに取り込む. This is the import primitive that a skill-scout/curator orchestrator calls; it does NOT discover or evaluate — it correctly imports ONE skill you already chose.