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 structured feasibility report. Use when a user brings a business question, asks 'can we answer this',…
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 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 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 Mcp Server
Repository hosting the open source Bauplan MCP server
Bauplan Safe Ingestion
Ingest data from S3 into Bauplan safely using branch isolation and quality checks before publishing. Use when loading new data from S3, importing parquet/csv/jsonl files, or when the user needs to safely load data with validation before merging to main.
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.