Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and 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。
929 件 ・ 関連度順
概要と使いどころ
Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and 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。
AI-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your 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 whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream tools.
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。
Preprocess CLIP-seq reads (eCLIP, iCLIP, iCLIP2, iCLIP3, irCLIP, PAR-CLIP, FLASH) with protocol-specific UMI extraction, adapter trimming, length filtering, and post-alignment PCR-duplicate collapse. Use when raw CLIP FASTQ must be turned into deduplicated, crosslink-preserving BAM input for peak calling; choosing between two-pass and single-pass adapter trimming; deciding minimum read length; or mapping UMI patterns to specific eCLIP/iCLIP/iCLIP2/iCLIP3 library preps.
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。
Extracts and assigns COSMIC v3.4 mutational signatures (84 SBS / 11 DBS / 18 ID / 24 CN / 16 SV) from somatic VCFs using SigProfilerSuite, MutationalPatterns, MuSiCal mvNMF, SigNet, or HRDetect. Use when characterizing DNA-damage etiology (BRCA1/2 HRD, MMR-D, POLE, APOBEC3A, UV, tobacco, aflatoxin, 5-FU/SBS17b, platinum, colibactin SBS88), routing PARP inhibitor decisions, or auditing de novo extraction vs refit choice for cohort size.
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。
Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and Reaction templates, with explicit handling of atom mapping, template extraction (RDKit reaction mining), product validation, RECAP/BRICS fragmentation, R-group decomposition, matched molecular pair analysis (MMPA), and Free-Wilson analysis. Use when generating combinatorial libraries from building blocks, enumerating analog series, deriving structure-activity rules, or extracting transformations from reaction data.
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。
Runbook for creating or majorly growing an @ai-matrx TypeScript npm package. Use when invoked as /new-package <name or capability>, or for a new @ai-matrx/* package, extracting code into one, or a major growth wave. NOT for a routine fix inside an existing package (THE SAME-SESSION LAW).
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 image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.
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。
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.
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. Use for multimodal content extraction from documents, images, audio, and 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。
AI-driven data extraction from 55+ Actors across all major platforms. This skill automatically selects the best Actor for your 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。
Optional vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, FindAll, and monitoring. Prefer JSON output and non-interactive 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。
Supply chain investigation, evidence recovery, and forensic analysis for GitHub repositories. Covers deleted commit recovery, force-push detection, IOC extraction, multi-source evidence collection, hypothesis formation/validation, and structured forensic reporting. Inspired by RAPTOR's 1800+ line OSS Forensics system.
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。
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
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。
Non-testing browser automation - web scraping, form filling, screenshot capture, PDF generation, workflow automation. For TESTING with Playwright, use e2e-playwright skill instead. Activates for web scraping, form automation, screenshot, PDF, headless browser, Puppeteer, Selenium, automation scripts, 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。
Intelligent pattern selection for Fabric CLI. Automatically selects the right pattern from 242+ specialized prompts based on your intent - threat modeling, analysis, summarization, content creation, extraction, and more. USE WHEN processing content, analyzing data, creating summaries, threat modeling, or transforming text.
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。
Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Google Search, Google Trends, Reddit, Airbnb, Yelp, and 15+ more platforms. Use for lead generation, brand monitoring, competitor analysis, influencer discovery, trend research, content analytics, audience analysis, review analysis, SEO intelligence, recruitment, or any data extraction 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。
Optional vendor skill for Parallel CLI — agent-native web search, extraction, deep research, enrichment, FindAll, and monitoring. Prefer JSON output and non-interactive 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。
Extract text from PDFs/scans (pymupdf, marker-pdf).
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 reverse engineer specializing in binary analysis, disassembly, decompilation, and software analysis. Masters IDA Pro, Ghidra, radare2, x64dbg, and modern RE toolchains. Handles executable analysis, library inspection, protocol extraction, and vulnerability research. Use PROACTIVELY for binary analysis, CTF challenges, security research, or understanding undocumented software.
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 malware analyst specializing in defensive malware research, threat intelligence, and incident response. Masters sandbox analysis, behavioral analysis, and malware family identification. Handles static/dynamic analysis, unpacking, and IOC extraction. Use PROACTIVELY for malware triage, threat hunting, incident response, or security research.
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。