claude

bauplan

Skills for working with Bauplan data lakehouses: explore data, build pipelines, ingest from object storage, debug failures, assess data feasibility, generate quality checks, and optimize DAGs

18 on GitHubby Bauplan Labsv2.6.0MITupdated 11 days ago
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Plugin bauplan from marketplace bauplan-skills in BauplanLabs/bauplan-skills. Commands read from the repo's manifest — 10 days ago.

What it installs

Skills (9)

  • bauplan-dag-optimization

    Optimizes an existing, poorly structured Bauplan DAG so it runs faster without changing its outputs. Reads the code and profiles the data, then restructures the models, decides what is materialized, narrows inputs with projections and filters, merges or splits projects, and proposes a data-driven pa

  • bauplan-data-assessment

    Assesses whether a business question can be answered with data available in a Bauplan lakehouse. Maps business concepts to tables and columns, checks data quality on the relevant subset, validates semantic fit, and renders a verdict: answerable, partially answerable, or not answerable. Produces a st

  • bauplan-data-pipeline

    Creates bauplan data pipeline projects with SQL and Python models. Use when starting a new pipeline, defining DAG transformations, writing models, or setting up bauplan project structure from scratch.

  • bauplan-data-quality-checks

    Generates data quality check code for bauplan pipelines and ingestion workflows. Invoked by the bauplan-data-pipeline and bauplan-safe-ingestion skills, or directly by the user. Produces expectations.py for pipelines or validation logic for WAP scripts. Output is always code, never reports.

  • bauplan-data-semantics

    Reads and drafts the semantic layer of a Bauplan lakehouse — the table-level and column-level documentation carried in Iceberg as `comment` and field `doc`. Use to find out what a column means before querying it, to diagnose a query that returned a plausible but wrong number, or to draft documentati

  • bauplan-debug-and-fix-pipeline

    Diagnose a failed Bauplan job, pin the exact data state, collect evidence, apply a minimal fix, and rerun. Evidence first, changes second.

  • bauplan-explore-data

    Explores data in a Bauplan lakehouse safely using the Bauplan Python SDK. Use to inspect namespaces, tables, schemas, samples, and profiling queries; and to export larger result sets to files. Read-only exploration only; no writes or pipeline runs.

  • bauplan-migrate-to-typed-sdk

    Migrates an existing bauplan pipeline project from the old SDK style (0.1.x or 0.2.x) to the typed SDK (0.3.+). Use when asked to migrate a pipeline to the new SDK, add type annotations to a bauplan project, upgrade to bauplan 0.3, or adopt TableSchema / the semantic layer.

  • bauplan-safe-ingestion

    Ingest data from object storage (S3 or GCS) into Bauplan safely using branch isolation and quality checks before publishing. Use when loading new data from S3 or GCS (s3:// or gs:// paths), importing parquet/csv/jsonl files, or when the user needs to safely load data with validation before merging t

View source on GitHub

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