Individual skill
palantir-core-workflow-a
Design and validate a Foundry Python transform pipeline with explicit datasets, compute choice, expectations, and incremental semantics. Use when building or changing batch data pipelines. Trigger with "Foundry transform" or "Palantir data pipeline".
skills/.curated/palantir-core-workflow-a/SKILL.md
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- ai Repository topic
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# Palantir Python Transform Pipeline
## Overview
Create a pipeline whose inputs, outputs, engine, write behavior, and quality checks are explicit before the first production build. Prefer the simplest supported compute engine that satisfies data scale and feature requirements, then prove the choice with Foundry metrics.
## Prerequisites
- Identify the owning project, Code Repository, input and output datasets, schema contract, data classification, and build schedule.
- Confirm whether the workload requires Spark or can use a single-node engine such as Polars, pandas, or DuckDB.
- Read `references/official-docs.md` and inspect current input transaction history before selecting incremental semantics.
- Develop on a sandbox branch with representative but appropriately protected data.
## Current Contract
