「capa」の検索結果

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。

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。

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。

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。

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。

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。

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。

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。

Converts a biomedical study storyline into a graphical abstract and, when direct image capability is available, generates the graphical abstract directly; otherwise it falls back to prompts, Mermaid flowcharts, or designer-facing briefs.

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 when the user asks what information a Stripe Connect connected account must provide for verification, onboarding, KYC, or account requirements; when they need to compare requirements between connected-account setups; or when they ask which verification fields, documents, or business details are required for a particular platform country, account country, business type, dashboard, service agreement, or capability.

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。

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 Codex'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。

Model OR-Tools paired pickup-and-delivery routing problems, including PDPTW, dial-a-ride, paratransit, patient transport, and courier jobs with same-vehicle pairing, precedence, capacity, optional connected service, rider time windows, and vehicle shifts.

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。

This skill includes search capability in 13F, such as fuzzy search a fund information using possibly inaccurate name, or fuzzy search a stock cusip info using its name.

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.

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。

Compare and implement eviction policies (LRU, LFU, FIFO, S3FIFO, ARC) for bounded-capacity caches. Use when choosing or implementing an eviction policy for a buffer pool, page cache, CDN edge, or LLM KV cache, or when writing a replay simulator that supports multiple policies. Clarifies recency vs frequency semantics, queue topology, saturating counters, ghost buffers, and the second-chance rule that distinguishes modern FIFO-family policies from classic LRU.

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。