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Found 1,703 Skills
Use when building features that answer questions from private data, documents, policies, or time-sensitive information — RAG architecture, chunking strategies, hybrid search, re-ranking, vector databases, evaluation, agentic RAG, multimodal RAG...
Use when service fails with Connection refused to database or redis. Use when API crashes because DB not ready.
Runs the Metabase semantic checker against a tree of Representation Format YAML files to verify that all references resolve — cross-entity references (collection_id, dashboard_id, parent_id, parameter source cards, snippet references, transform tags, etc.) and references to columns inside MBQL and native queries. Use when the user asks to "semantic check", "check references", "validate queries against the schema", or diagnose a broken reference. Requires database metadata on disk (by default `.metabase/metadata.json`).
Use this skill whenever working with QuestDB — a high-performance time-series database. Trigger on any mention of QuestDB, time-series SQL with SAMPLE BY, LATEST ON, ASOF JOIN, ILP ingestion, or the questdb Python/Go/Java/Rust/.NET client libraries. Also trigger when writing Grafana queries against QuestDB, creating materialized views for time-series rollups, working with order book or financial market data in QuestDB, or any SQL that involves designated timestamps or time-partitioned tables. QuestDB extends SQL with unique time-series keywords — standard PostgreSQL or MySQL patterns will fail. Always read this skill before writing QuestDB SQL to avoid hallucinating incorrect syntax.
Designs and implements data layer architecture for Magento 2. Use when creating data models, designing database schemas, implementing repositories, or working with EAV/flat table structures. Masters entity design, repository patterns, collections, and database optimization.
Implement AI Coaching best practices on AnalyticDB for PostgreSQL (ADBPG): Leverage Supabase projects (training data management) + ADBPG instances with vector optimization to build RAG-driven coaching systems that guide users through domain-specific workflows, decision-making, or skill development. Use when: User wants to create Supabase projects (spb-xxx), ADBPG instances (gp-xxx), vector knowledge bases, or RAG-driven coaching systems on ADBPG. Triggers: "Supabase", "ADBPG", "vector database", "knowledge base", "RAG", "AI coaching", "coaching system", "spb-xxx", "gp-xxx"
Cloudflare Vectorize vector database for semantic search and RAG. Use for vector indexes, embeddings, similarity search, or encountering dimension mismatches, filter errors.
Generate a Wren MDL project by exploring a database with available tools (SQLAlchemy, database drivers, MCP connectors, or raw SQL). Guides agents through schema discovery, type normalization, and MDL YAML generation using the wren CLI. Use when: user wants to create or set up a new MDL, onboard a new data source, or scaffold a project from an existing database.
Use Ibis for database-agnostic data access in Python. Use when writing data queries, connecting to databases (DuckDB, PostgreSQL, SQLite), or building portable data pipelines that should work across backends.
Performance and scalability analysis specialist. Identifies algorithmic inefficiencies, N+1 queries, memory leaks, and concurrency issues. Use when reviewing loops, database queries, file I/O, or high-concurrency code.
Detect and fix SQL injection vulnerabilities in any framework. Covers Laravel (DB::raw, whereRaw), Node.js (template literals in queries), Python (f-strings in SQL), and Cloudflare D1. Enforces parameterized bindings everywhere. Use when writing database queries, reviewing code for injection, or fixing SQL injection findings.
Build with Firestore NoSQL database - real-time sync, offline support, and scalable document storage. Use when: creating collections, querying documents, setting up security rules, handling real-time listeners, or troubleshooting permission-denied, quota exceeded, invalid query, or offline persistence errors. Prevents 10 documented errors.