Results for “mongodb”

Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.

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Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.

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Decision and migration guide for Prisma ORM MongoDB projects on v6, which have no upgrade path to v7. Use when a MongoDB project asks about upgrading Prisma, when "upgrade to prisma 7" comes up in a project with provider = "mongodb", or when evaluating a move to Prisma 8. Triggers on "upgrade prisma mongodb", "prisma 7 mongodb", "mongodb prisma migration", "prisma 8 mongodb".

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Design MongoDB data structures around how data is accessed, write queries, and build staged data transformations for aggregation. Review indexes and query execution statistics to identify performance issues and choose suitable approaches for related or time-series data.

• Choosing between embedded and referenced data
• Writing search queries and aggregation pipelines
• Reviewing slow queries and index usage

Use when you need to add or review Mongock MongoDB data migrations in a Spring Boot application — including Maven coordinates, Spring Data MongoDB drivers, migration scan packages, @ChangeUnit classes, lock/transaction settings, and optional policy-approved MongoDB integration verification. This should trigger for requests such as Add Mongock migrations in Spring Boot; Review Spring MongoDB data migrations; Configure Mongock change units for Spring Data MongoDB; Create Mongock change units for Spring Boot MongoDB; Review Mongock migration ordering in a Spring service. Part of Plinth Toolkit

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Create a MongoDB CDC capture using flowctl. Use when setting up real-time streaming from MongoDB Atlas, DocumentDB, or self-hosted MongoDB. Use when user says "capture MongoDB", "stream from Mongo", "MongoDB CDC", or "connect MongoDB to Estuary".

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Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.

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Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.

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使用火山引擎 MongoDB Skill，帮助用户完成 MongoDB 相关的实例管理、备份恢复、参数等运维任务，可直接调用 uv run ./scripts/call_mongodb.py 脚本获取实时结果。当需要访问管理在火山引擎 MongoDB 实例详细信息时，此 Skill 可以提供方便的接口。

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Use when you need to add or review Mongock MongoDB data migrations in a Micronaut application — including Mongock runner/driver selection, Micronaut bean wiring, migration scan packages, @ChangeUnit classes, lock/transaction settings, and Testcontainers verification. This should trigger for requests such as Add Mongock migrations in Micronaut; Review Micronaut MongoDB data migrations; Configure Mongock change units with Micronaut Data MongoDB; Create Mongock change units for Micronaut MongoDB; Review Mongock migration ordering in a Micronaut service. Part of Plinth Toolkit

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Use when you need to design or implement MongoDB data access in Spring Boot — including document modeling, Spring Data Mongo repositories/templates, indexing, optimistic concurrency, and error handling. This should trigger for requests such as Add MongoDB in Spring Boot; Review Spring Data Mongo design; Improve error handling for Mongo writes; Model MongoDB documents for a Spring Boot service; Configure Spring Data MongoDB indexes or transactions. Part of Plinth Toolkit

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Use when you need MongoDB persistence in Quarkus — including Panache Mongo entities/repositories, document design, indexes, transactions where applicable, and error handling. This should trigger for requests such as Add MongoDB in Quarkus; Review Quarkus Mongo Panache design; Improve Mongo error handling in Quarkus services; Model MongoDB documents for a Quarkus service; Configure Quarkus MongoDB clients codecs or transactions. Part of Plinth Toolkit

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Use when you need MongoDB persistence in Micronaut — including @MongoRepository design, document modeling, indexes, query patterns, and error handling. This should trigger for requests such as Add MongoDB in Micronaut; Review Micronaut Data Mongo design; Improve error handling for Micronaut Mongo operations; Model MongoDB documents for a Micronaut service; Configure Micronaut MongoDB codecs indexes or transactions. Part of Plinth Toolkit

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Use when you need to add or review Mongock MongoDB data migrations in a Quarkus application — including the Quarkiverse Mongock extension, Quarkus MongoDB client configuration, migrate-at-start, @ChangeUnit classes, lock/transaction settings, and Quarkus test verification. This should trigger for requests such as Add Mongock migrations in Quarkus; Configure quarkus-mongock; Review Quarkus MongoDB data migrations; Create Mongock change units for Quarkus MongoDB; Review Mongock migration ordering in a Quarkus service. Part of Plinth Toolkit

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Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: "How do I optimize this query?", "How do I index this?", "Why is this query slow?", "Can you fix my slow queries?", "What are the slow queries on my cluster?", etc. Do not invoke for general MongoDB query writing unless user asks for performance or index help. Prefer indexing as optimization strategy. Use MongoDB MCP when available.

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Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.

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Guide users through configuring key MongoDB MCP server options. Use this skill when a user has the MongoDB MCP server installed but hasn't configured the required environment variables, or when they ask about connecting to MongoDB/Atlas and don't have the credentials set up.

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Complete guide for Testcontainers NoSQL integration testing. Use when containerized integration testing for MongoDB or Redis. Covers MongoDB document operations, Redis five data structures, Collection Fixture pattern. Includes BSON serialization, index performance testing, data isolation strategy, and container lifecycle management. Keywords: testcontainers mongodb, testcontainers redis, mongodb integration test, redis integration test, nosql testing, MongoDbContainer, RedisContainer, IMongoDatabase, IConnectionMultiplexer, BSON serialization, BsonDocument, document model testing, cache testing, Collection Fixture

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Create a Spring Boot Java project skeleton with Maven, database connection settings, and Docker Compose services. Adds dependencies for API documentation and architecture tests, then checks the generated project with a Maven test command.

• Start a Java 21 Spring Boot project
• Prepare local PostgreSQL, Redis, and MongoDB services
• Add API documentation and architecture test dependencies

Investigate and fix agent behavior in TradingAgentsCN by checking active database prompt templates, prompt assembly code, and output processing. Apply targeted changes and verify them with focused tests, template checks, and workflow logs.

• Investigating prompt changes that do not affect runtime behavior
• Synchronizing database templates with prompt assembly code
• Tracing incorrect dates or price references in position analysis

Manage MongoDB Atlas Organizations as Azure ARM resources using Azure.ResourceManager.MongoDBAtlas SDK. Use when creating, updating, listing, or deleting MongoDB Atlas organizations through Azure Marketplace integration. This SDK manages the Azure-side organization resource, not Atlas clusters/databases directly.

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Manages Amazon DocumentDB end-to-end — serverless-on-8.0 cluster setup, TLS/VPC/driver config, flexible-schema and vector-search data modeling, MongoDB compatibility assessment, DMS-based migration, slow-query diagnosis, major version upgrades (4.0->5.0->8.0), Well-Architected reviews (41-check wa_review.py), cost estimation, and security hardening. Retrieve for every DocumentDB question and when the user asks to set up or migrate MongoDB to AWS — DocumentDB is AWS's MongoDB-compatible managed database. Triggers: JSON document store, document database, MongoDB on AWS, Nested fields, Lambda cannot connect, TLS handshake, VPC port 27017, IAM auth, Secrets Manager, encryption at rest, $graphLookup, flexible schema, COLLSCAN, compound index, DMS migration, CDC cutover, $vectorSearch, RAG, Global Clusters, DR replication, cost sizing, audit, health check, production-readiness.

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Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.

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Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: "How do I optimize this query?", "How do I index this?", "Why is this query slow?", "Can you fix my slow queries?", "What are the slow queries on my cluster?", etc. Do not invoke for general MongoDB query writing unless user asks for performance or index help. Prefer indexing as optimization strategy. Use MongoDB MCP when available.

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