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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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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".

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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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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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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.

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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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Azure deployment for web apps — Static Web Apps, App Service, Blob Storage, Bicep/ARM, GitHub Actions CI/CD. Use when deploying Next.js/Vite to Azure or configuring Azure resources for full-stack apps.

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Expert en Elasticsearch (indexing, mappings, aggregations, Kibana, DSL queries)

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Data Analyst IA — Expert en analyse de données (SQL, BI dashboards, Metabase, Superset, reporting, KPIs)

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Database Architect IA — Expert en conception de bases de données (PostgreSQL, MongoDB, Redis, schema design, migrations). Optimise le stockage et l'accès aux données.

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Expert en bases de données (PostgreSQL, MySQL, MongoDB, Redis, query optimization, replication)

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Coolify Specialist IA — Expert en Coolify (self-hosting, Docker, SSL, backups, one-click apps, migration)

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Backend Python Specialist IA — Expert en développement backend Python (FastAPI, Django, SQLAlchemy, Celery, async, type safety)

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Backend Node.js Specialist IA — Expert en développement backend Node.js (Express, Fastify, NestJS, Prisma, real-time, WebSockets)

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Use this skill when writing aggregation pipelines, grouping, joining collections, or optimizing slow MongoDB queries. Trigger words: 集計, aggregate, パイプライン, $group, $lookup, $match, 結合, グループ化, 遅いクエリ, explain.

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Use this skill when starting a new session, opening this project for the first time, or when you need to recall the project's tech stack, hard rules, and which other skills exist. Trigger words: セッション開始, このプロジェクト, 全体像, どのスキル, 何から, getting started, overview.

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Use this skill when implementing full-text search, autocomplete, or vector/semantic search and RAG with MongoDB Atlas. Trigger words: 全文検索, あいまい検索, オートコンプリート, ベクトル検索, セマンティック検索, 類似検索, Atlas Search, $search, $vectorSearch, RAG, embedding.

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Use this skill whenever user-controlled input flows into a MongoDB query, filter, or update. Trigger words: NoSQL Injection, ユーザー入力, req.body, クエリに渡す, find, filter, spread, $where, 検索条件, security review.

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Use this skill when designing MongoDB schemas, defining Mongoose models, choosing embed-vs-reference, or adding indexes. Trigger words: スキーマ設計, モデル定義, Mongoose, コレクション, インデックス, 埋め込み, 参照, embed, reference, index.

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This skill should be used when the user asks to "search for exposed devices on the internet," "perform Shodan reconnaissance," "find vulnerable services using Shodan," "scan IP ranges with Shodan," or "discover IoT devices and open ports." It provides comprehensive guidance for using Shodan's search engine, CLI, and API for penetration testing reconnaissance.

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Manage MongoDB Atlas Organizations as Azure ARM resources with unified billing through Azure Marketplace.

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Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions.

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bu skill covers implementing Gitleaks for Tespit etme and preventing hardcoded secrets in git repositories. It addresses configuring pre-commit hooks, CI/CD pipeline integration, custom rule authoring for organization-specific secrets, baseline management for existing repositories, and remediation workflows for exposed credentials.

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Tests APIs for mass assignment (auto-binding) vulnerabilities where clients can modify object properties they should not have Erişim: by including additional parameters in API requests. The tester identifies writable endpoints, adds undocumented fields to request bodies (role, isAdmin, price, balance), and checks if the server binds these to the data model without filtering. Part of OWASP API3:2023 Broken Object Property Level Authorization. Activates for requests involving mass assignment ...

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