Loading...
Loading...
Found 26 Skills
Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing tests, or evaluating impact of changes. Use for analytics pipelines, data transformations, and data modeling.
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with $helpers, working with dates using DateTime, troubleshooting Code node errors, or choosing between Code node modes.
Guide for creating GreptimeDB Pipeline, by which user can add a process layer to GreptimeDB between ingestion and storage, to transform data.
Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.
Use when analyzing FileMaker DDR to extract calculations, custom functions, and business logic for PostgreSQL import processes or maintenance scripts - focuses on understanding and adapting FileMaker logic rather than direct schema migration
Extracts specific fields from JSON files efficiently using jq instead of reading entire files, saving 80-95% context. Use this skill when querying JSON files, filtering/transforming data, or getting specific field(s) from large JSON files
JSON querying, filtering, and transformation with jq command-line tool. Use when working with JSON data, parsing JSON files, filtering JSON arrays/objects, or transforming JSON structures.
Consult this skill when designing data pipelines or transformation workflows. Use when data flows through fixed sequence of transformations, stages can be independently developed and tested, parallel processing of stages is beneficial. Do not use when selecting from multiple paradigms - use architecture-paradigms first. DO NOT use when: data flow is not sequential or predictable. DO NOT use when: complex branching/merging logic dominates.
Coaches users to transform messy data into clean, analysis-ready formats using Power Query UI. Diagnoses data problems, visualizes goals, and guides step-by-step transformations.
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
Ingest and transform data files (CSV/JSON/Parquet/Arrow IPC) into Elasticsearch with stream processing, custom transforms, and cross-version reindexing. Use when loading files, batch importing data, or migrating indices across versions — not for general ingest pipeline design or bulk API patterns.