What problem does it solve? Writing valid query definitions for the Rierino low-code platform requires knowing its exact JSON schema, query types, and condition operators. This Skill translates plain-language data requests into complete, schema-compliant query objects, removing manual JSON authoring errors. ## Core Features & Use Cases - Query Type Inference: Automatically selects SIMPLE, AGGREGATION, BUNDLE, or PIPELINE types based on the request, across MongoDB, SQL, Elasticsearch, and other database systems. - Structured Filter Trees: Builds recursive where conditions with logical combinators (AND/OR/NOT), comparison operators, set membership, and unary checks. - Aggregations and Pipelines: Produces grouped metrics (COUNT, SUM, AVG, MAX, MIN) and multi-stage pipeline steps for complex transformations. - Use Case: Ask to "get average and total revenue per country from sales where year is 2024" and receive a ready-to-save AGGREGATION query JSON, which can then be persisted to the Rierino platform via the MCP server after your approval. ## Quick Start Ask the assistant to build a Rierino query that finds all shipped orders with totals above 100 sorted by date descending.
