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Found 5,513 Skills
Firebase development guidelines for Firestore, Authentication, Functions, and Storage with TypeScript and Angular.
Graph database implementation for relationship-heavy data models. Use when building social networks, recommendation engines, knowledge graphs, or fraud detection. Covers Neo4j (primary), ArangoDB, Amazon Neptune, Cypher query patterns, and graph data modeling.
Learn how to deploy PocketBase on Google Cloud Run using the new volume mounting feature, enabling scale-to-zero, infinite storage, and easy backups.
Synchronize the base44-sdk skill with the latest SDK source code from the Base44 SDK repository
This skill should be used when configuring Supabase Auth for server-side rendering with Next.js App Router, including secure cookie handling, middleware protection, route guards, authentication utilities, and logout flow. Apply when setting up SSR auth, adding protected routes, implementing middleware authentication, configuring secure sessions, or building login/logout flows with Supabase.
Build AI that answers questions about your database. Use when you need text-to-SQL, natural language database queries, a data assistant for non-technical users, AI-powered analytics, plain English database search, or a chatbot that talks to your database. Covers DSPy pipelines for schema understanding, SQL generation, validation, and result interpretation.
Use when researching, segmenting, and maintaining journalist/analyst contact lists.
Architecture and design review for specified files/dirs/repo. Covers tech debt, patterns, quality. Diff-only review use review-diff. Complements review-code (orchestrated).
Use this skill when you need to alter the PocketBase database schema - creating, updating, or deleting collections. Never write migration SQL by hand.
Automatically discover database skills when working with SQL, PostgreSQL, MongoDB, Redis, database schema design, query optimization, migrations, connection pooling, ORMs, or database selection. Activates for database design, optimization, and implementation tasks.
Vector database selection, embedding storage, approximate nearest neighbor (ANN) algorithms, and vector search optimization. Use when choosing vector stores, designing semantic search, or optimizing similarity search performance.
Instructions for using the DeepBase multi-driver persistence library. Use when a task requires data persistence, storage abstraction, multi-backend setups, data migration between drivers, or integrating DeepBase into a Node.js project.