creating-bauplan-pipelines
Create Bauplan Data Pipelines
Bauplan projects need clear DAG structure, branch safety, and consistent SQL or Python model patterns. This skill guides Claude, Codex, and Claude Code through pipeline files, validation, and safe run workflows.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "creating-bauplan-pipelines" from https://skillstore.io/skills/bauplanlabs-creating-bauplan-pipelines.md and its manifest at https://skillstore.io/api/skills/bauplanlabs-creating-bauplan-pipelines/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "creating-bauplan-pipelines". Create a taxi trip pipeline with zone enrichment and a daily summary output.
Expected outcome:
- A Bauplan project plan with source tables, DAG order, and final materialized outputs.
- A SQL first node for lakehouse reads and Python models for enrichment and summary logic.
- A dry-run checklist that verifies branch, source tables, and materialization settings.
Using "creating-bauplan-pipelines". Add quality checks for order identifiers and trip distance values.
Expected outcome:
- Expectation functions for non-null identifiers, unique identifiers, and reasonable distance values.
- Guidance for strict-mode runs so expectation failures stop the pipeline early.
Using "creating-bauplan-pipelines". Review my Bauplan model plan before I run it.
Expected outcome:
- A review of SQL versus Python model placement, output columns, and I/O pushdown usage.
- A list of required confirmations before running state-changing Bauplan commands.
Security Audit
Medium RiskThe static findings are false positives from markdown backticks, Python import examples, table samples, and assertion text. I found one contextual medium risk: user-provided branch and table identifiers are inserted into Bauplan CLI and SQL preview commands without validation guidance.
Confirmed security concerns (1)
Risk Factors
⚡ Contains scripts (1)
⚙️ External commands (60)
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<a href="https://skillstore.io/skills/bauplanlabs-creating-bauplan-pipelines?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/bauplanlabs-creating-bauplan-pipelines/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/bauplanlabs-creating-bauplan-pipelines.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
BauplanLabs. (2026). creating-bauplan-pipelines security audit report (audit version 8) [Author version unspecified]. Skillstore. https://skillstore.io/skills/bauplanlabs-creating-bauplan-pipelines/audits/8BibTeX citation
@techreport{bauplanlabs-bauplanlabs-creating-bauplan-pipelines-2026,
author = {BauplanLabs},
title = {creating-bauplan-pipelines security audit report (audit version 8)},
institution = {Skillstore},
year = {2026},
number = {8},
url = {https://skillstore.io/skills/bauplanlabs-creating-bauplan-pipelines/audits/8},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "creating-bauplan-pipelines security audit report (audit version 8)"
version: "unspecified"
type: report
authors:
- name: "BauplanLabs"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/bauplanlabs-creating-bauplan-pipelines/audits/8"
identifiers:
- type: other
value: "skillstore:bauplanlabs-creating-bauplan-pipelines:audit:8"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Start a New Analytics Pipeline
Create a Bauplan project with source nodes, transformations, materialized outputs, and a dry-run workflow.
Convert Business Logic into Models
Turn transformation requirements into SQL source models and Python downstream models with clear DAG dependencies.
Add Data Quality Checks
Define expectations, output schemas, and strict-mode checks before publishing pipeline results.
Try These Prompts
Create a Bauplan pipeline for [goal] using source table [table]. Ask me for missing branch, output, and materialization details before writing files.
Build a Bauplan DAG for [business logic]. Use SQL only for first source reads, then use Python models with declared output columns.
Create a multi-input Bauplan model that joins [table A] and [table B]. Use I/O pushdown, docstrings, and materialized final outputs.
Review this Bauplan pipeline for branch safety, materialization choices, strict mode, expectations, and schema validation. Suggest fixes before any run.
Best Practices
- Use a development branch and run a dry run before any full pipeline run.
- Declare output columns and use I/O pushdown for every model when possible.
- Confirm materialization strategy for each final table before running the pipeline.
Avoid
- Running pipeline commands on the main branch.
- Using SQL models for downstream transformations after the first lakehouse read.
- Leaving branch names, table names, or SQL preview queries unchecked before execution.
Frequently Asked Questions
What does this skill create?
Does it run pipelines automatically?
Which assistants can use it?
Can it write both SQL and Python models?
Does it require existing source tables?
How does it handle data quality?
Developer Details
Author
BauplanLabsLicense
MIT
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
5ab1d37e83436c6eef84de88573e142b94f2a4ad
Maintenance freshness
7/20/2026
Usage
4 downloads · 281 views
File structure
📄 SKILL.md