2,978 件 ・ 関連度順
概要と使いどころ
Build reliable web scrapers and crawlers with Crawlee — Apify's open-source framework for structured web scraping. Use when someone asks to "scrape a website", "build a crawler", "Crawlee", "web scraping at scale", "scrape JavaScript-rendered pages", "crawl with Playwright/Puppeteer", or "extract data from websites reliably". Covers HTTP crawling, browser crawling, request queues, proxy rotation, and data export.
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。
Browser Use is an open-source Python library that lets an LLM agent drive a real browser to navigate sites, fill forms, click and extract data from a plain-English task. Use when the user wants an AI agent to automate a website, scrape pages that need clicking or login, return structured data from the web, add browser tools to a coding agent, or run browser agents locally or in the cloud.
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。
Generate waveform visualizations from audio files. Use when a user asks to create waveform images, build audio player visualizations, generate waveform data for web players, create podcast episode previews, build audio thumbnails, render waveform PNGs for social media, extract peak data as JSON, or integrate waveform generation into audio processing pipelines. Covers audiowaveform CLI, JSON/binary data output, and web player integration.
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。
Builds HTTP APIs and web services in Rust with Axum, the Tokio team's web framework on top of Tokio, Hyper and Tower. Use when a user asks to create a Rust REST API, add routes, extractors, JSON handlers, shared state, middleware, error handling, WebSockets, graceful shutdown or tests with Axum, or to migrate older Axum code (0.6/0.7 path syntax) to 0.8.
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。
Actix Web is a powerful, high-performance web framework for Rust. It provides async handlers, type-safe extractors, middleware, and integrates with the Rust ecosystem for building fast, reliable, and memory-safe web services.
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 detailed ideal customer profiles with pain points, objections, buying triggers, and messaging angles. Includes community research to find where ICPs gather online and extract their exact language. Use when researching audiences, creating buyer personas, or developing targeted messaging.
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。
Extract and analyze competitor advertising from public ad libraries (Facebook Ad Library, Google Ads Transparency Center, TikTok, LinkedIn). Identifies messaging patterns, creative formats, pain points targeted, and positioning gaps. Use for competitive intelligence, campaign planning, and creative inspiration.
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。
Patterns for building multimodal AI applications that combine text, images, audio, and video. Covers vision APIs, audio transcription, and unified pipelines. Use when "multimodal AI, vision API, image understanding, GPT-4V, Claude vision, audio transcription, Whisper, document extraction, image to text, " mentioned.
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 in understanding and navigating legacy codebases. Covers code archaeology techniques, finding hidden knowledge, mapping dependencies, and extracting understanding from code without documentation. Knows how to read the stories that old code tells. Use when "legacy code, old codebase, understand this code, archaeology, what does this do, no documentation, ancient code, " mentioned.
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 reviewing contracts, extracting key terms, identifying risks, or building contract analysis tools - covers NLP approaches, clause identification, and risk scoringUse when ", " mentioned.
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。
Extract clean markdown content from web pages using Defuddle CLI, removing clutter and navigation to save tokens. Use instead of WebFetch when the user provides a URL to read or analyze, for online documentation, articles, blog posts, or any standard web page.
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。
Extract action items as plain markdown bullets (with confirmation). Args: <path>. No args = run [/note-status pending --step=todos](../note-status/SKILL.md#pending-mode).
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。
Azure AI Content Understanding SDK for Python workflow skill. Use this skill when the user needs Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Azure.AI.DocumentIntelligence (.NET) workflow skill. Use this skill when the user needs Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
AWS Penetration Testing workflow skill. Use this skill when the user needs Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Azure AI Content Understanding SDK for Python workflow skill. Use this skill when the user needs Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
AWS Penetration Testing workflow skill. Use this skill when the user needs Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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。
Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/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。
Web取得の標準前処理レイヤー。URL・公式ドキュメント・ブログ・ニュース・OSSページを読むときは、原則として毎回このSkillでDefuddleを使い本文をMarkdown/JSON化してから読む。生HTMLのまま要約・分析・比較・レビューしない。トリガー例: URLを読む/Webページ要約/OSS調査/公式Doc確認/記事解析/競合サイト確認/Web一次情報確認。
Convert raster images (photos, paintings, illustrations, line art) into SVG vector reproductions. Use when the user uploads an image and asks to reproduce, vectorize, trace, or convert it to SVG. Also use when asked to decompose an image into shapes, create an SVG version of a picture, or faithfully reproduce artwork as vector graphics. Handles graphic/line-art inputs (Kandinsky, architectural drawings, ink work) via a compositional pipeline that extracts lines as SVG strokes. Do NOT use for creating original SVG illustrations from text descriptions — only for converting existing raster images.
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。
Skill-aware orchestration with context routing. Decomposes complex tasks into skill-typed subtasks, extracts targeted context subsets, executes subagents in parallel, and synthesizes results. Self-answers trivial lookups inline. No SDK dependency — uses raw HTTP via httpx. Use when tasks require multiple analytical perspectives, when context is large and subtasks only need portions, or when orchestrating-chat-agents spawns too many redundant subagents.
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。
DEPRECATED — superseded by tree-sitting. This skill generated persistent _MAP.md files; tree-sitting does the same AST extraction at runtime (~700ms for 250 files) with no artifact to write, commit, or keep in sync. Use tree-sitting for "map this codebase", "explore repo", "understand structure", or any code navigation task. The final working version is archived at release mapping-codebases-v0.8.0.
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。
In-process semantic search over text files or in-memory strings, using Gemini embeddings via the CF AI Gateway. Use when user wants fuzzy/conceptual search where exact-keyword grep would miss — "sessions discussing regulatory constraints", "code about retry logic", "notes mentioning burnout even if the word isn't there". Complements searching-codebases (regex/AST) and extracting-keywords (YAKE). Do NOT use when an exact string/regex match is what's wanted — grep/rg wins on speed and precision there.
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。
Analyzes an AI/ML publication — paper, preprint, article, technical blog post — and extracts what an enterprise AI engineer should do about it. Use when someone supplies a URL or document on RAG, embeddings, fine-tuning, prompt engineering, agents, or LLM deployment and asks "review this paper", "what do you make of this", "is this worth adopting", or "summarise the method and its limits". The subject matter must itself be machine learning.
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。