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prefect-flow-builder skill

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/skills/11-data-pipelines/prefect-flow-builder

This skill helps you implement prefect flow builder tasks with step-by-step guidance, production-ready code, and best practices for data pipelines.

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill prefect-flow-builder

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: "prefect-flow-builder"
description: |
  Build prefect flow builder operations. Auto-activating skill for Data Pipelines.
  Triggers on: prefect flow builder, prefect flow builder
  Part of the Data Pipelines skill category. Use when working with prefect flow builder functionality. Trigger with phrases like "prefect flow builder", "prefect builder", "prefect".
allowed-tools: "Read, Write, Edit, Bash(cmd:*), Grep"
version: 1.0.0
license: MIT
author: "Jeremy Longshore <[email protected]>"
---

# Prefect Flow Builder

## Overview

This skill provides automated assistance for prefect flow builder tasks within the Data Pipelines domain.

## When to Use

This skill activates automatically when you:
- Mention "prefect flow builder" in your request
- Ask about prefect flow builder patterns or best practices
- Need help with data pipeline skills covering etl, data transformation, workflow orchestration, and streaming data processing.

## Instructions

1. Provides step-by-step guidance for prefect flow builder
2. Follows industry best practices and patterns
3. Generates production-ready code and configurations
4. Validates outputs against common standards

## Examples

**Example: Basic Usage**
Request: "Help me with prefect flow builder"
Result: Provides step-by-step guidance and generates appropriate configurations


## Prerequisites

- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of data pipelines concepts


## Output

- Generated configurations and code
- Best practice recommendations
- Validation results


## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |


## Resources

- Official documentation for related tools
- Best practices guides
- Community examples and tutorials

## Related Skills

Part of the **Data Pipelines** skill category.
Tags: etl, airflow, spark, streaming, data-engineering

Overview

This skill automates creation and guidance for Prefect flow builder operations focused on data pipelines. It produces step-by-step instructions, production-ready code snippets, and configuration artifacts to accelerate workflow orchestration tasks. The skill is auto-activating for requests mentioning Prefect flow builder and integrates data pipeline best practices.

How this skill works

On trigger, the skill inspects your intent and pipeline context to generate Prefect flows, tasks, and deployment configurations. It follows common patterns for ETL, transformations, streaming, and scheduling, and validates outputs against typical standards (naming, dependencies, retries). The skill can produce runnable Python code, Docker/infra hints, and concise validation notes.

When to use it

You need to scaffold a new Prefect flow or refactor an existing one.
You want production-ready Prefect tasks with retries, timeouts, and logging.
You need deployment config examples for Prefect Orion/Prefect Cloud.
You want guidance on orchestrating ETL, streaming, or transformation pipelines.
You need to validate flow structure, dependencies, or common anti-patterns.

Best practices

Define small, idempotent tasks and compose them into clear flows.
Use retries, timeouts, and circuit-breaker patterns for external calls.
Parameterize flows for environments and secrets; avoid hard-coded credentials.
Add observability: structured logs, metrics, and clear task naming conventions.
Validate DAGs locally and include unit tests for critical task logic.

Example use cases

Scaffold a Prefect flow for daily ETL: extract from S3, transform with Pandas, load to a database.
Add robust retry and timeout behavior to tasks that call external APIs.
Generate deployment config and Dockerfile for running flows on Prefect agents or cloud.
Refactor a monolithic pipeline into modular Prefect tasks with clear dependencies.
Create streaming ingestion flows that checkpoint state and handle backpressure.

FAQ

What inputs do you need to generate a flow?

Provide data sources, target destinations, key transformation steps, schedule, and any environment constraints or credentials management preferences.

Can you produce code that runs on Prefect Cloud or local Orion?

Yes. I can generate flow code and deployment examples tailored to Prefect Orion or Prefect Cloud, including Docker tips and agent configuration.