929 件 ・ 関連度順
概要と使いどころ
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
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。
Smart browser task agent - describe what you want done in natural language and it completes automatically. PREFERRED tool for multi-step browser operations like searching, form filling, and data extraction.
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。
Analyze images using Dashscope (Qwen) Vision models for detailed description, OCR text extraction, object recognition, and visual Q&A. Use when the user needs to understand image content via Alibaba Cloud Dashscope API, especially for Chinese-language image analysis and documents.
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 subtitles and transcripts from Bilibili and YouTube videos. Use when the user wants to get subtitles from B站 (Bilibili) or YouTube, extract Chinese/Japanese video transcripts, watch member-only Bilibili content, or perform Q&A on video content. Supports dual-platform subtitle extraction with yt-dlp.
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。
Douyin (TikTok China) content toolkit for video script writing, short video optimization, BGM recommendations, caption generation, trending topic analysis, and video download/info extraction workflows.
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。
Analyze images using GPT-4 Vision for detailed description, OCR text extraction, object recognition, and visual Q&A. Use when the user needs to understand image content, extract text from screenshots, identify objects in photos, or ask questions about images via OpenAI GPT-4 Vision 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。
PaddleOCR text recognition skill using PP-OCRv5 lightweight model. Supports natural scene and complex document text detection and recognition. Use when user needs OCR text extraction from 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。
Web data extraction using 55+ Apify Actors for AI-driven scraping. Supports Instagram, Facebook, TikTok, YouTube, Google, and more. Auto-selects best Actor for the task. Structured output in JSON/CSV with rate limiting and ethical scraping guidelines.
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。
Orchestrates a systematic review and meta-analysis workflow following PRISMA 2020 guidelines, from protocol development through multi-database search, screening, data extraction, and evidence synthesis. Use when conducting evidence-based reviews, meta-analyses, or scoping revi...
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 the Methods section for a meta-analysis paper, including search strategy, screening, quality assessment, data extraction, and statistical analysis.
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 complete FAERS-style pharmacovigilance disproportionality research designs from a user-provided drug class, comparator strategy, adverse-event domain, and patient-group stratification. Always use this skill whenever a user wants to design, plan, or build a spontaneous-report safety signal study using FAERS or a similar pharmacovigilance database, especially when the article logic includes product selection, indication-group stratification, MedDRA-based adverse-event extraction, serious-case filtering, suspect-drug and concomitant-exclusion logic, reporting odds ratio analysis, comparator-drug benchmarking, cross-drug comparison, and cautious signal interpretation without causal overclaiming. Covers five study patterns (single-drug disproportionality workflow, multi-drug class comparison workflow, indication-stratified workflow, comparator-controlled signal screening 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。
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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。
Drive feature development using Outside-In TDD with Hexagonal Architecture. Design emerges through inline code, in-memory fakes, interface extraction, and deferred I/O. Use when building features, writing tests, or structuring backend services. Triggers on: TDD, outside-in, hexagonal, ports and adapters, emergent design, acceptance test, component test, walking skeleton, in-memory fakes, component, contract test, adapter, fast tests, sub-second feedback. Language-agnostic (Go, Rust, Python, TypeScript, Java, C#).
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。
Rasa NLU pipeline configuration and training for intent and entity extraction
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。
spaCy NER model training and entity extraction for conversational AI
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。
Save URLs with auto-extracted insights, credibility scoring, and vault routing
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。
Pattern extraction, confidence-scored evaluation, skill creation, organization, versioning, and cross-project export pipeline.
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 CVSS (Common Vulnerability Scoring System) scores from vulnerability data sources with proper fallback handling. This skill covers understanding CVSS v3, handling multiple score sources (NVD, GHSA, RedHat), implementing source priority logic, and dealing with missing scores in security reporting.
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 key frames (I-frames) from video files using FFmpeg command line tool. Use this skill when the user needs to pull out keyframes, thumbnails, or important frames from MP4, MKV, AVI, or other video formats for analysis, previews, or processing.
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 document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks
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 OR-Tools RoutingModel vehicle-routing models with transit matrices, dimensions, capacity constraints, time windows, optional visits, invalid-arc handling, search parameters, and route extraction.
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Estimate heart rate (HR) and breathing rate (BR) in bpm from a cleaned 1-D physiological time series such as radar phase, WiFi CSI amplitude, PPG, or a chest-motion signal. Use when Claude needs to choose HR/BR bandpass edges, pick a peak frequency from a noisy band, reject the HR second harmonic that often dominates the fundamental, handle respiration-harmonic leakage into the HR band on slow breathers, or flag low-confidence estimates. Not for arrhythmia / beat-to-beat analysis, multi-subject source separation, or rapidly non-stationary rates.
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Use for formulating, solving, debugging, and validating mixed-integer linear optimization models with open-source solvers, including variable indexing, sparse constraints, linearized costs, solver limits, MIP gaps, incumbent extraction, numerical tolerances, and deterministic output reporting.
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Multi-hop evidence search + structured extraction over enterprise artifact datasets (docs/chats/meetings/PRs/URLs). Strong disambiguation to prevent cross-product leakage; returns JSON-ready entities plus evidence pointers.
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。