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Found 63 Skills
Design NoSQL database schemas for MongoDB and DynamoDB. Use when modeling document structures, designing collections, or planning NoSQL data architectures.
Build React applications using React Router's data mode with createBrowserRouter and RouterProvider. Use when working with route objects, loaders, actions, Form, useFetcher, or pending/optimistic UI without the Vite plugin.
Comprehensive Pydantic data validation skill for customer support tech enablement - covering BaseModel, Field validation, custom validators, FastAPI integration, BaseSettings, serialization, and Pydantic V2 features
Design systems, services, and architectures. Trigger with "design a system for", "how should we architect", "system design for", "what's the right architecture for", or when the user needs help with API design, data modeling, or service boundaries.
Create and manage NocoBase data models via MCP. Use when users want to inspect or change collections, fields, relations, or view-backed schemas in a NocoBase app.
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.
SQL database queries, joins, aggregations, subqueries, and optimization. Use for .sql files and database operations.
AWS DynamoDB NoSQL database for scalable data storage. Use when designing table schemas, writing queries, configuring indexes, managing capacity, implementing single-table design, or troubleshooting performance issues.
Load automatically when planning, researching, or implementing ANY Medusa backend features (custom modules, API routes, workflows, data models, module links, business logic). REQUIRED for all Medusa backend work in ALL modes (planning, implementation, exploration). Contains architectural patterns, best practices, and critical rules that MCP servers don't provide.
Best practices for building with Gadget. Use when developers need guidance on models, actions, routes, access control, Shopify/BigCommerce integrations, frontend patterns, API usage, permissions, or framework decisions. Triggers "model", "action", "route", "permission", "access control", "multi-tenancy", "Shopify", "BigCommerce", "frontend", "API client", "filter", "pagination", "webhook", "background job"
Orchestrates the full journey from zero to a running Neo4j application. Executes 8 named stages in order: prerequisites → context → provision → model → load → explore → query → build. Each stage has its own reference file in references/ that the agent reads and follows when entering that stage. Supports both HITL and fully autonomous operation. Time budget: ≤15 min after DB is running (autonomous), ≤90 min total (HITL).
Qdrant vector database: collections, points, payload filtering, indexing, quantization, snapshots, and Docker/Kubernetes deployment.