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概要と使いどころ
Connect an MCP-capable coding agent to OpenChatCut and edit local video projects. Use when the user asks to install, connect, or set up OpenChatCut; inspect or edit an OpenChatCut project; work with its timeline, transcript, captions, media, generation, motion graphics, audio, color, or export tools; or recover from an OpenChatCut MCP error.
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。
Define a dataset's metadata profile — infer a Frictionless Table Schema from its data, add Data Package metadata (license, sources, keywords), and write it into datasets.json so the showcase renders a typed field table. Extend or customize via the L0-L3 profile ladder. Use when a registered dataset needs field types, constraints, or catalog metadata before publishing.
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 developing WordPress plugins: architecture and hooks, activation/deactivation/uninstall, admin UI and Settings API, data storage, cron/tasks, security (nonces/capabilities/sanitization/escaping), and release packaging.
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 or update Claude skills. Use for new skills, skill references, skill scripts, optimizing existing skills, extending Claude's capabilities.
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 Shopify applications, extensions, and themes using GraphQL/REST APIs, Shopify CLI, Polaris UI components, and Liquid templating. Capabilities include app development with OAuth authentication, checkout UI extensions for customizing checkout flow, admin UI extensions for dashboard integration, POS extensions for retail, theme development with Liquid, webhook management, billing API integration, product/order/customer management. Use when building Shopify apps, implementing checkout customizations, creating admin interfaces, developing themes, integrating payment processing, managing store data via APIs, or extending Shopify functionality.
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。
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
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。
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
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 creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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 multiple DeepSeek Harness plugin Skills across inspection, migration, runtime debugging, heavy dependencies, testing, naming, and release. Use for a guided lifecycle workflow, a pre-run capability menu, or several DSH plugin operations with one status report. Preserve the user's selected scope and existing authorization across stages.
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。
Writes and revises agent skills so they trigger at the right moments and give usable instruction when they do. Use this when creating a new skill, editing an existing one, diagnosing a skill that fires too often or never fires, or reviewing a set of skills for overlap. Also use before adding to a skill library, to check the capability is not already covered.
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。
Owns architecture, engineering delivery, infrastructure, data platform, and internal systems. Use this for build-versus-buy calls, technology selection, architectural direction, engineering capacity and delivery risk, technical debt tradeoffs, platform and tooling decisions, or when a technical choice has business consequences that need stating in business terms. Also use to judge whether a technical plan is sound before it is committed to.
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 and maintains the design system a product is assembled from — tokens for color, type, spacing and elevation, component contracts, and the rules that keep them coherent as the product grows. Use this when starting a new interface, when screens have drifted apart visually, when the same component exists three times in slightly different forms, or when a token or component needs adding without breaking what exists.
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。
Runs servers and corporate systems — patching, configuration baselines, change control, capacity, and the routine that prevents incidents. Use this to establish a patching cadence, standardize server configuration, plan a maintenance window, decide change control for infrastructure, or clean up systems that have drifted from any known state.
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。
Runs the hypervisor layer beneath the servers — host capacity and consolidation ratios, VM sprawl, snapshot discipline, resilience and live migration, and licensing that counts cores rather than instances. Use this to size or expand a cluster, work out why VMs are slow when the hosts look idle, clean up sprawl, set snapshot and template policy, or decide what stays virtualized and what moves to 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。
Owns data as an asset — governance, quality, the warehouse and semantic layer, analytics capability, and the governance of models built on top. Use this for a decision about how data is collected, stored, defined, or shared; when numbers disagree between teams; when deciding what to build in-house versus buy; when standing up a data function; or when an AI or model decision needs governance rather than engineering.
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 for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart". Multiple LLM reviewers challenge changes from independent angles.
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。
Get MCP server detailed usage instructions (INSTRUCTIONS.md). When you need to understand server full capabilities or learn server-specific usage patterns.
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。
Get skill detailed instructions and usage guide (Level 2 disclosure). When you need to understand how to use a skill, check skill capabilities, or learn skill parameters.
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。
Call MCP server tool for extended capabilities. Check 'MCP Servers' section in system prompt for available servers and tools. When you need to use external service or access specialized functionality.
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 this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
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。
Baidu FaMou algorithm skills for efficient algorithm self-evolution. Provides experiment management and visualization capabilities to help optimize complex algorithms. Use when user needs algorithm optimization or experiment management.
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。
Baidu Yijian visual management skill for industrial scenarios. Provides visual recognition capabilities across 20+ industries including retail, energy, mining, ports, chemical, and steel. Use for industrial visual inspection and management.
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 formatting references for journal submission, converting between citation styles (APA, MLA, Vancouver, Chicago), generating bibliographies for manuscripts, or ensuring consistent reference formatting. Automatically formats citations and bibliographies in 1000+ academi...
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。