「sql」の検索結果

Python backend expert including Django, FastAPI, Flask, SQLAlchemy, and async patterns

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Use when you need to auto-log all tool interactions into a self-organizing vector DB with instant recall. Intercepts interactions, extracts key information, generates embeddings, stores in LanceDB, auto-categorizes, and builds a retrieval index. Inspired by OpenClaw SQLite LCM + summary DAG pattern.

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。

Rules for Drizzle ORM schema design, query patterns, migration workflows, and relational query usage. Ensures type-safe, production-ready database interactions.

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。

Database design and optimization specialist. Schema design, query optimization, indexing strategies, data modeling, and migration planning for relational and NoSQL databases.

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。

Scaffolds PostgreSQL database component with migrations, seeds, and management scripts.

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。

PostgreSQL database standards for migrations, seeds, and schema 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。

D2 diagramming language reference for architecture diagrams, sequence diagrams, grid layouts, SQL tables, and class diagrams. Produces .d2 files rendered via CLI or playground.

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。

Configure and manage Supabase projects using MCP (Model Context Protocol). Use this skill when working with Supabase databases, setting up MCP servers, designing database schemas, implementing Row Level Security, managing migrations, or building modern data architectures with PostgreSQL. Essential for Supabase development, database design, and AI-powered database 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。

Discover, message, and coordinate AI coding agents (Claude Code, Codex CLI) running on the same machine via a shared Unix socket broker backed by SQLite. The broker wakes recipients natively (Claude inbox socket, codex queue) and turn-boundary hooks catch missed wakes. Supports cross-session task delegation, peer summaries, and session lifecycle management. Triggers on 'peer agents', 'cross-session communication', 'message Codex', 'inter-agent messaging', 'coordinate agents'.

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 queries on the Postgres database. Use this skill DIRECTLY whenever the user asks anything about database contents, counts, or data — do NOT read compose.yml or SQL migration files first.

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 the user needs to design, run, or audit product or GTM analytics — metric hierarchies and north stars, funnels, cohort retention, churn, pipeline velocity, forecasting, lead scoring, NRR, A/B tests, or analytical SQL — or uploads a dataset to analyze. Triggers on questions like "why did activation drop", "is this metric meaningful", "review my dashboard", or "what should I measure". For writing the spec that defines a feature's success metrics, use product-spec.

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。

xUnit, Moq/NSubstitute, FluentAssertions, and coverlet patterns for any .NET project. Covers test structure ([Fact]/[Theory]/[InlineData]), mocking discipline, fluent assertions, integration test setup with WebApplicationFactory, and coverage measurement. Stack-agnostic — referenced by every .NET plugin in the marketplace. Use this skill to: - Write clear, maintainable unit tests with xUnit [Fact] and [Theory]. - Mock dependencies with Moq or NSubstitute without overusing mocks. - Write expressive assertions with FluentAssertions. - Measure coverage with coverlet and enforce a minimum threshold. Do NOT use this skill for: - ASP.NET Core-specific integration tests (WebApplicationFactory, HttpClient — those are in aspnet-core-plugin:aspnet-conventions). - EF Core in-memory or SQL Server LocalDB test patterns (aspnet-core-plugin:efcore-patterns). - C# language idioms — see csharp-foundation:csharp-conventions.

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。

ORM patterns for NestJS: TypeORM, Prisma, Mongoose. Covers entities, repositories, transactions, migrations, common pitfalls (N+1, cascade deletes, transaction boundaries). Use this skill to: - Detect which ORM the project uses and apply matching patterns. - Define entities/schemas with the right decorators. - Inject repositories or Prisma client correctly. - Run transactions at the service boundary. - Write migrations that round-trip cleanly. Do NOT use this skill for: - Module/DI patterns (see nest-conventions). - Decorator usage broadly (see decorator-patterns). - Non-ORM raw SQL (rare; flag in BLOCKERS if needed).

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 a human-curated dbt model index must guide BigQuery SQL for a warehouse question. Not for discovering undocumented models or executing warehouse changes.

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。

Connect to and query ClickHouse (a local server or a ClickHouse Cloud service) from the terminal. For ClickHouse Cloud analytics, use the configured direct ClickHouse Query API endpoint with per-user CH_API_KEY and CH_API_SECRET credentials; do not use clickhousectl cloud service query. For local or host/port servers, use clickhousectl local client. Use when the user wants to run SQL against ClickHouse, explore schemas and tables, inspect Cloud services, or authenticate. For building a local dev environment or deploying to Cloud, defer to the official ClickHouse skills (see 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。

Save, organize, and describe reusable analysis artifacts such as SQL, result snapshots, CSV exports, summaries, caveats, plots, and report-ready files. Use when users ask to save, export, share, cite, reproduce, or organize data-analysis outputs.

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。

Read project data documentation (data dictionaries, dbt manifests, model docs, column descriptions, lineage, metric definitions) before writing analytics SQL. Use for mapping business and product terms to concrete models and columns.

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。

Act as an interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse 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。

Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.

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 these skills to manage and monitor Oracle databases by executing SQL statements, exploring schema metadata, analyzing query performance, monitoring active sessions and resource consumption, and managing storage and object health.

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。

Act as an interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse 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。

Save, organize, and describe reusable analysis artifacts such as SQL, result snapshots, CSV exports, summaries, caveats, plots, and report-ready files. Use when users ask to save, export, share, cite, reproduce, or organize data-analysis outputs.

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 Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, SDK usage, and vector search. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database 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。

Read project data documentation (data dictionaries, dbt manifests, model docs, column descriptions, lineage, metric definitions) before writing analytics SQL. Use for mapping business and product terms to concrete models and columns.

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。