「schemas」の検索結果

Automate Close CRM tasks via Rube MCP (Composio): create leads, manage calls/SMS, handle tasks, and track notes. Always search tools first for current schemas.

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。

Automate Canva tasks via Rube MCP (Composio): designs, exports, folders, brand templates, autofill. Always search tools first for current schemas.

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。

Automate Calendly scheduling, event management, invitee tracking, availability checks, and organization administration via Rube MCP (Composio). Always search tools first for current schemas.

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。

Automate Cal.com tasks via Rube MCP (Composio): manage bookings, check availability, configure webhooks, and handle teams. Always search tools first for current schemas.

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。

Automate Bitbucket repositories, pull requests, branches, issues, and workspace management via Rube MCP (Composio). Always search tools first for current schemas.

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。

Automate Basecamp project management, to-dos, messages, people, and to-do list organization via Rube MCP (Composio). Always search tools first for current schemas.

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。

Automate BambooHR tasks via Rube MCP (Composio): employees, time-off, benefits, dependents, employee updates. Always search tools first for current schemas.

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。

Automate Asana tasks via Rube MCP (Composio): tasks, projects, sections, teams, workspaces. Always search tools first for current schemas.

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。

Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.

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。

Automate Amplitude tasks via Rube MCP (Composio): events, user activity, cohorts, user identification. Always search tools first for current schemas.

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。

Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.

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。

Validate implementation prerequisites, load slice/spec context, detect execution mode, and write contract schemas before TDD execution

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 working with Cube Dev — cube.dev semantic layer management — monitor deployments, data models, pre-aggregations, query performance, and API health. Use when inspecting cube schemas, debugging slow queries, reviewing pre-aggregation builds, or auditing API usage.

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 working with Convex — convex backend platform management covering project inventory, table schemas, function deployments, scheduled job status, index configuration, environment variable auditing, and usage metrics. Use for comprehensive Convex project health and resource optimization.

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 doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).

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。

T-SQL, stored procedures, and MS SQL Server DBA practices. Use when writing SQL queries, designing schemas, tuning SQL Server performance, managing backups, configuring security, or using SQL Server 2025+ features.

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。

MongoDB with Mongoose — schemas, models, aggregation pipelines, migrations, and Atlas connections. Use when designing collections, writing queries, or integrating MongoDB into Node.js/Next.js apps.

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。

MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".

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。

Power BI semantic models - DAX measures, star schemas, relationships, RLS, and performance tuning via MCP. Use when creating data models, writing DAX, or configuring table relationships in Power BI.

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。

Automate Sentry tasks via Rube MCP (Composio): manage issues/events, configure alerts, track releases, monitor projects and teams. Always search tools first for current schemas.

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。

Automate Supabase database queries, table management, project administration, storage, edge functions, and SQL execution via Rube MCP (Composio). Always search tools first for current schemas.

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 guidance for designing, implementing, migrating, and debugging SwiftData persistence in Swift and SwiftUI apps. Use when working with @Model schemas, @Relationship/@Attribute rules, Query or FetchDescriptor data access, ModelContainer/ModelContext configuration, CloudKit sync, SchemaMigrationPlan/history APIs, ModelActor concurrency isolation, or Core Data to SwiftData adoption/coexistence.

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。

Integrate on-device AI using Foundation Models framework, Core ML, and open-source LLM runtimes on Apple Silicon. Covers Foundation Models (LanguageModelSession, @Generable, @Guide, SystemLanguageModel, structured output, tool calling), Core ML (coremltools, model conversion, quantization, palettization, pruning, Neural Engine, MLTensor), MLX Swift (transformer inference, unified memory), and llama.cpp (GGUF, cross-platform LLM). Use when building tool-calling AI features, working with guided generation schemas, converting models, or running on-device inference.

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。

Implement App Intents for Siri, Shortcuts, Spotlight, widgets, Control Center, and Apple Intelligence on iOS. Covers AppIntent actions, AppEntity and EntityQuery models, AppShortcutsProvider phrases, IndexedEntity Spotlight indexing, WidgetConfigurationIntent, SnippetIntent, and assistant schemas. Use when exposing app actions or entities to system surfaces.

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。