「database」の検索結果

Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation.

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。

Creates integration test cases for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Generates DB-agnostic xUnit tests with deterministic seed data that validate behavior consistency across both database systems. Use when creating integration tests for a migrated project, generating test coverage for data access layers, or writing Oracle-to-PostgreSQL migration validation 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。

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

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。

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

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。

Notion API + ntn CLI: pages, databases, markdown, Workers.

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。

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems. Use PROACTIVELY for database optimization or complex analysis.

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 in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similarity search. Use PROACTIVELY for vector search implementation, embedding optimization, or semantic retrieval systems.

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。

.NET advanced testing skills overview and navigation center. Triggered when users ask about "integration testing", "API testing", "containerized testing", "microservice testing", "test framework migration", "Testcontainers", "Aspire testing", and other advanced testing needs. Recommends appropriate sub-skills based on specific requirements, covering integration testing, Testcontainers, Aspire testing, framework upgrades, and other 8 advanced skills. Keywords: integration testing, integration testing, API testing, advanced testing, advanced testing, testcontainers, aspire testing, WebApplicationFactory, TestServer, database test, database testing, EF Core test, MongoDB test, Redis test, Docker test, container testing, microservice test, microservice testing, .NET Aspire, xUnit upgrade, TUnit, framework migration

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。

Detect and exploit NoSQL injection vulnerabilities in MongoDB, CouchDB, and other NoSQL databases to demonstrate authentication bypass, data extraction, and unauthorized access risks.

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。

Detect OS credential dumping techniques targeting LSASS memory, SAM database, NTDS.dit, and cached credentials using EDR telemetry, Sysmon process access monitoring, and Windows security event correlation.

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。

Detecting and exploiting SQL injection vulnerabilities using sqlmap to extract database contents during authorized penetration 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。

Sets up vector databases for semantic search including Pinecone, Chroma, pgvector, and Qdrant with embedding generation and similarity search. Use when users request "vector database", "semantic search", "embeddings storage", "Pinecone setup", or "similarity search".

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。

Audits database schemas for naming conventions, type consistency, nullability patterns, and missing constraints. Provides violations report with recommended fixes. Use for "schema validation", "database linting", "schema standards", or "consistency checks".

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。

Defines database performance monitoring strategy with slow query detection, resource usage alerts, query execution thresholds, and automated alerting. Use for "database monitoring", "performance alerts", "slow queries", or "DB metrics".

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。

Generates deterministic seed data for development and testing with factory functions, realistic fixtures, and database reset scripts. Use for "data seeding", "test fixtures", "database seeding", or "mock data generation".

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。

SQL injection testing skill for offensive security assessments and bug bounty hunting. Covers error-based, UNION-based, boolean/time-based blind, out-of-band, second-order, NoSQL, GraphQL, WebSocket, and JSON-operator SQLi. Includes WAF bypass techniques, database-specific exploitation (MySQL, MSSQL, PostgreSQL, Oracle), cloud-native attack paths, ORM CVE tracking, and SQLmap automation. Use when performing web application SQL injection testing, database enumeration, privilege escalation via SQLi, or assessing injection vectors in APIs and modern stacks.

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。

You are helping a penetration tester enumerate database services and check for

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。

Firebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong. Firestore queries are limited, and you learn this after you've designed your data model. This skill covers Firebase Authentication, Firestore, Realtime Database, Cloud Functions, Cloud Storage, and Firebase Hosting. Key insight: Firebase is optimized for read-heavy, denormalized data. I

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。

Saga patterns, compensating actions, and two-phase commit for distributed transactions. Activate on: distributed transaction, saga, compensating action, two-phase commit, eventual consistency, cross-service transaction. NOT for: single-database transactions (use database-connection-pool-manager), event sourcing (use cqrs-event-sourcing-architect).

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。

Architect data fetching with TanStack Query v5, SWR, optimistic updates, prefetching, and cache invalidation strategies. Activate on: React Query, SWR, optimistic updates, cache invalidation, prefetching, stale-while-revalidate, infinite queries. NOT for: REST API design (use api-architect), database queries (use database skills), GraphQL schema (use graphql-expert).

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。

Application architecture patterns and code organization — clean architecture, hexagonal architecture, feature-based structure, dependency inversion, module boundaries, SOLID principles at module scale. Activate on "clean architecture", "hexagonal architecture", "feature-based structure", "dependency inversion", "module boundaries", "architecture pattern", "folder structure", "fat controller", "circular dependency", "IoC container". NOT for microservice decomposition (use microservices-patterns) or database schema design (use database-design-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。

運用者が設定したTeamサーバーの更新を、指定担当のNight Watchに引き継ぎ、既存の更新機構による検証・復旧・完了確認まで進めるスキル。

• Teamを公式mainへ更新したいとき
• 失敗・延期した更新の続行調整
• データベース移行と復旧の調整

Granolaのローカルアーカイブから会議メモや文字起こしを検索・取得するスキル。同期状態を確認し、必要な更新やSQLによる正確な件数集計も扱います。

• 話題から過去の会議メモを探したいとき
• メモの文字起こしやパネルの取得
• 最近の情報を調べる前の同期状態確認

NotionのページをMarkdownで取得・作成・更新し、データの絞り込みや検索を行います。ファイル、コメント、Workersの操作も扱うスキルです。

• Markdownからページを作成・更新したいとき
• データベースの記録を絞り込みたいとき
• ページ検索やコメント確認をしたいとき