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Found 36 Skills
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.
Structured data extraction from web pages using claude-in-chrome MCP with sequential-thinking planning. Focus on READ operations, data transformation, and pagination handling for multi-page extraction.
Convert between physical units (length, mass, temperature, time, etc.). Use for scientific calculations, data transformation, or unit standardization.
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
Analyze and transform CSV data using bash tools
Advanced Juicebox data migration strategies. Use when migrating from other recruiting platforms, performing bulk data imports, or implementing complex data transformation pipelines. Trigger with phrases like "juicebox data migration", "migrate to juicebox", "juicebox import", "juicebox bulk migration".
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.
This spell is about representation change, not: - Naming changes (same structure, different identifiers) - Execution changes (same code, different runtime) - Architecture changes (new system design) - Duplication (same thing, different place) The key test: Can you point to a source artifact and a target artifact where the same information is expressed in structurally different ways? If yes → Polymorph.
Prefect Flow Builder - Auto-activating skill for Data Pipelines. Triggers on: prefect flow builder, prefect flow builder Part of the Data Pipelines skill category.
Write field mappings and transforms in Celigo integrations. Covers Mapper 2.0 (imports), Transformation 2.0 (exports), lookups, response mapping, and Mapper 1.0 (NetSuite/Salesforce). Use when editing mappings[], transform{}, responseMapping, or lookup configurations.
Use when the user reaches for a Code node, mentions writing JavaScript or Python in n8n, or any custom logic comes up in workflow design. Triggers on "Code node", "Code", "JavaScript", "Python", "custom logic", "transform data", "$input", "$json transformation", "loop in code", "write a function", or any time the obvious answer seems to be "just put it in code."
Process large datasets efficiently using chunk(), chunkById(), lazy(), and cursor() to reduce memory consumption and improve performance