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documentdb-driver

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Aktualisiert4. Mai 2026 um 19:04

MongoDB driver and SDK best practices for Azure DocumentDB — singleton `MongoClient`, connection reuse, connection-pool fundamentals. Use when writing code that instantiates a MongoDB client, reviewing driver initialization, or diagnosing connection-related bugs. For full connection-pool tuning (serverless vs OLTP vs OLAP, timeouts, retries), see the `documentdb-connection` skill.

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Azure

Azure/documentdb-agent-kit

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SoftwareentwicklerInformatik- und Mathematikberufe·SOC 15-1252

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SKILL.md

readonly

name	documentdb-driver
description	MongoDB driver and SDK best practices for Azure DocumentDB — singleton `MongoClient`, connection reuse, connection-pool fundamentals. Use when writing code that instantiates a MongoDB client, reviewing driver initialization, or diagnosing connection-related bugs. For full connection-pool tuning (serverless vs OLTP vs OLAP, timeouts, retries), see the `documentdb-connection` skill.
license	MIT

Driver Best Practices — Azure DocumentDB

MongoDB driver usage patterns that apply across Node.js, Python, Java, Go, and .NET. For in-depth pool-size / timeout / retry tuning, see the documentdb-connection skill.

Rules

driver-singleton-client — Reuse MongoClient as a process-wide singleton; never create a new client per request.

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documentdb-mcp-setup

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Guide users through installing and configuring the DocumentDB MCP server for Azure DocumentDB. Use this skill when a user wants to wire the DocumentDB MCP server into an agentic client (Claude Code, Claude Desktop, Cursor, Copilot CLI, Gemini CLI, VS Code) and define a `CONNECTION_PROFILES` entry, or when they hit MCP connection / auth / profile errors.

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documentdb-connection

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Optimize MongoDB client connection configuration (pools, timeouts, patterns) for Azure DocumentDB. Use this skill when working on functions that instantiate or configure a MongoDB client (e.g., calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing connection-related performance issues. Includes scenarios like building serverless functions, creating API endpoints, optimizing high-traffic applications, or debugging connection failures.

2026-05-265

documentdb-full-text-search

Azure/documentdb-agent-kit

Full-text search best practices for Azure DocumentDB using the `createSearchIndexes` command and `$search` aggregation stage — BM25 keyword scoring, fuzzy search (`maxEdits`), phrase search with `slop`, custom analyzers (keyword + lowerCase + asciiFolding + edgeGram) for prefix / ID matching, `pathHierarchy` tokenizer for hierarchical IDs, multi-field search indexes, and hybrid (BM25 + vector) retrieval via Reciprocal Rank Fusion. Use when building search experiences, adding typo tolerance, matching phrases or prefixes on IDs / SKUs / part numbers, or combining lexical and semantic retrieval on the same collection.

2026-05-265

documentdb-vector-search

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Vector search best practices for Azure DocumentDB using `cosmosSearch` — choosing between DiskANN / HNSW / IVF, creating indexes, tuning `lBuild` / `lSearch` / `maxDegree`, Product Quantization (up to 16,000 dims), half-precision (fp16) indexing, and normalizing embeddings for cosine similarity. Use when building RAG / semantic-search applications, creating a vector index, tuning recall/latency, or reducing vector-index memory footprint.

2026-05-265

documentdb-indexing

Azure/documentdb-agent-kit

Index-type selection and shape guidance for Azure DocumentDB — when to use single-field, compound (ESR), multikey, wildcard, hashed, 2dsphere, TTL, and vector indexes; query-pattern → index-shape cookbook; per-collection index budget; DocumentDB-specific preference for `textSearch` over community `$text`. Use when designing or reviewing indexes, choosing an index type for a query pattern, or deciding whether an additional index is worth the write cost.

2026-05-185

documentdb-natural-language-querying

Azure/documentdb-agent-kit

Generate read-only DocumentDB/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 queries for Azure DocumentDB, wants to filter/query/aggregate data, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT analyze or optimize existing queries — use documentdb-query-optimizer for that. Requires DocumentDB MCP server.

2026-05-185

name	documentdb-driver
description	MongoDB driver and SDK best practices for Azure DocumentDB — singleton `MongoClient`, connection reuse, connection-pool fundamentals. Use when writing code that instantiates a MongoDB client, reviewing driver initialization, or diagnosing connection-related bugs. For full connection-pool tuning (serverless vs OLTP vs OLAP, timeouts, retries), see the `documentdb-connection` skill.
license	MIT

Driver Best Practices — Azure DocumentDB

MongoDB driver usage patterns that apply across Node.js, Python, Java, Go, and .NET. For in-depth pool-size / timeout / retry tuning, see the documentdb-connection skill.

Rules

driver-singleton-client — Reuse MongoClient as a process-wide singleton; never create a new client per request.