「data」の検索結果

Azure Cosmos DB SDK for Java. NoSQL database operations with global distribution, multi-model support, and reactive 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。

Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models.

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。

Scrape e-commerce data for pricing intelligence, customer reviews, and seller discovery across Amazon, Walmart, eBay, IKEA, and 50+ marketplaces. Use when user asks to monitor prices, track competi...

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。

Deploy web apps with backend APIs, database, and file storage. Use when the user asks to deploy or publish a website or web app and wants a public URL. Uses HTTP API via curl.

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 Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.

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, tables, and structured data from documents using Azure Document Intelligence (@azure-rest/ai-document-intelligence). Use when processing invoices, receipts, IDs, forms, or building cu...

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 WhatsApp automations with Kapso workflows: configure WhatsApp triggers, edit workflow graphs, manage executions, deploy functions, and use databases/integrations for state. Use when automatin...

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。

Develop, debug, and deploy Apify Actors - serverless cloud programs for web scraping, automation, and data processing. Use when creating new Actors, modifying existing ones, or troubleshooting Acto...

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, Google Maps, Google Search, Google Trends, Booking.com, and TripAdvisor. Use for lead gener...

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 production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

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。

Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.

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Use for Nauthilus Lua plugins, Lua callback tests, policy compiler and registry work, Lua environment and subject sources, Lua actions, hooks, backend scripts, policy facts, obligation targets, `server/lualib`, `server/lua-plugins.d`, `server/policy`, and JSON fixtures under `testdata/lua`.

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 Nauthilus authentication and identity-provider work touching OIDC, OAuth2, SAML, MFA, TOTP, WebAuthn, recovery codes, LDAP-backed identity, browser login and consent flows, token/session/flow state, `private_key_jwt`, introspection, discovery metadata, endpoint-specific client authentication, and security-sensitive auth tests.

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。

Plan or review FriendlyBet architecture, implementation, schema, data flows, scoring, provider integrations, static/PWA behavior, Supabase/RLS impact, migrations, automation, and technical sequencing. Use when a task asks how to build, refactor, generalize, integrate, test, or safely ship FriendlyBet code.

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 sports rules, event formats, prediction types, scoring implications, lock rules, data requirements, and provider constraints for FriendlyBet. Use when adding or comparing sports such as football, basketball, American football, tennis, tournaments, leagues, playoffs, brackets, weekly picks, or World Cup-specific logic.

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。

Orchestrate operational workspace setup before implementation slices across scaffold, CI/CD, hosting, and data provisioning shards

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。

Execute per-layer adversarial audit/remediation loop, persist fixes metadata, and manage fresh-run advancement

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 or refresh docs/ARCHITECTURE.md from current codebase state with evidence-backed component and data-flow mapping

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Systematic methodology for verifying that IA, BE, and FE specification layers are mutually consistent. Covers coverage matrices, field mapping checks, error code propagation, access control consistency, and data contract drift detection.

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 codebase structure, data flow, module relationships, and key patterns to generate and maintain a living architecture document (ARCHITECTURE.md).

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 system architecture, error architecture, and data strategy with map guards and ideation context reload

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。

Bootstrap a new Gradle module in any Kotlin Android project. Walks the user through choosing one of three module types — library module (`com.android.library`), feature module (regular Android library that hosts a feature/UI, install-time only), or dynamic feature module (`com.android.dynamic-feature`, on-demand/conditional/instant delivery). Use whenever the user wants to add a module, modularize code, extract a util/data/ui layer, create a new feature, set up Play Feature Delivery, or asks "should this be a library or feature module?". Discovers the project's existing conventions (plugin aliases, namespaces, sibling modules, version catalog) instead of hardcoding any. Pushes back on bad combos (e.g. utility code in a dynamic feature). Stops at scaffolding; app-level wiring is out of scope.

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 Kotlin Compose design tokens from one of three supported sources — Google Stitch (MCP), Figma (MCP or JSON), or Claude Design (kta-design-spec output, Claude HTML/markdown artifacts). Three-layer architecture (Primitive/Semantic/Component) with code generation. Use when user asks to "generate design tokens", "create theme from Figma/Stitch/Claude design", "build Compose tokens from design spec", or "convert design source to tokens". Refuses any other input source and asks user for correct seed 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。

Create Kotlin Compose design tokens from one of three supported sources — Google Stitch (MCP), Figma (MCP or JSON), or Codex Design (kta-design-spec output, Codex HTML/markdown artifacts). Three-layer architecture (Primitive/Semantic/Component) with code generation. Use when user asks to "generate design tokens", "create theme from Figma/Stitch/Codex design", "build Compose tokens from design spec", or "convert design source to tokens". Refuses any other input source and asks user for correct seed 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。