Communitygithub.com

mongodb/agent-skills

Nutze die offiziellen MongoDB Skills mit deinem bevorzugten Coding-Agenten, um schneller zu bauen.

Was ist agent-skills?

Dieses Skill-Paket ermöglicht es Coding-Agenten wie Claude Code, Cursor oder Codex, direkt mit MongoDB zu interagieren, um Datenbankoperationen schneller und zuverlässiger durchzuführen. Es enthält vorgefertigte Anleitungen und Kontextinformationen, die dem Agenten helfen, MongoDB-spezifische Aufgaben wie das Erstellen von Abfragen, das Verwalten von Indizes oder das Debuggen von Aggregations-Pipelines effizient umzusetzen. Entwickler sparen Zeit, da der Agent nicht erst aus allgemeinem Wissen lernen muss, sondern auf optimierte Best Practices und offizielle MongoDB-Dokumentation zugreift. Das Projekt ist als Open-Source-Sammlung von Skill-Definitionen organisiert, die in verschiedenen Agent-Plattformen eingebunden werden können, um eine konsistente und fehlerärmere Entwicklungsarbeit zu gewährleisten.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add mongodb/agent-skills
Original anzeigen→Alle Skills durchsuchen

In Ihrer bevorzugten KI fragen

Öffnet einen neuen Chat, in dem dieser Agent-Skill bereits geladen ist.

OpenAIChatGPTClaudeClaudeGeminiGeminiGrokGrokPerplexityPerplexityDeepSeekDeepSeek

Dokumentation

Was macht agent-skills?

Nutze die offiziellen MongoDB Skills mit deinem bevorzugten Coding-Agenten, um schneller zu bauen.

Überblick

Dieses Repository enthält eine Sammlung von Skills, die speziell für Coding-Agenten entwickelt wurden, um MongoDB-Operationen zu optimieren. Jeder Skill ist als Markdown-Datei definiert und enthält Kontext, Beispiele und bewährte Methoden.

Verwendung

  1. Skill importieren – Lade die entsprechende Markdown-Datei in deinen Agenten (z. B. über claude-code).
  2. Agent anweisen – Weise den Agenten an, den Skill für MongoDB-Aufgaben zu verwenden.
  3. Automatisiert arbeiten – Der Agent nutzt das Wissen aus dem Skill, um Abfragen, Indizes oder Aggregations-Pipelines zu erstellen.

Unterstützte Agenten

  • Claude Code
  • Cursor
  • Codex (GitHub Copilot)
  • und andere konfigurierbare Agenten

Beispiele

# Beispiel: Mit dem Skill "mongodb-query-optimization"
Agent -> Erstelle einen Index für die Abfrage: db.users.find({ age: { $gt: 21 } })

Lizenz

Dieses Projekt steht unter der MIT-Lizenz.

Individual skills in this repo

This repo contains 6 individual skills — each has its own dedicated page.

mongodb/mongodb-connection

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.

mongodb/mongodb-mcp-setup

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.

mongodb/mongodb-natural-language-querying

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.

mongodb/mongodb-query-optimizer

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.

mongodb/mongodb-schema-design

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".

mongodb/mongodb-search-and-ai

Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.

Verwandte Skills

steipete/sag

ElevenLabs text-to-speech with mac-style say UX.

community

steipete/oracle

Oracle CLI second-model review/debug/refactor/design with selected files, dry-run token checks, API or browser engine.

community

steipete/peekaboo

Capture and automate macOS UI with the Peekaboo CLI.

community

mattpocock/design-an-interface

Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".

community

mattpocock/prototype

Build a throwaway prototype to flesh out a design — a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.

community

mattpocock/grill-me

Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".

community