airflow-dag-patterns

Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

Install with Tessl CLI

npx tessl i github:sickn33/antigravity-awesome-skills --skill airflow-dag-patterns

What are skills?

Review — 75%

Does it follow best practices?

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npx tessl skill review --optimize ./path/to/skill

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Evaluation — 92%

Agent success when using this skill

Validation — 10 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

Evaluation results

100%

Daily Transaction Ingestion Pipeline

Production DAG configuration defaults

Criteria

Without context

With context

retries=3

100%

retry_delay 5 min

100%

exponential backoff

100%

max_retry_delay

100%

email_on_failure True

100%

email_on_retry False

100%

depends_on_past False

100%

catchup=False

100%

max_active_runs=1

100%

DAG tags

100%

No hardcoded dates

100%

on_failure_callback

100%

Without context: $0.4272 · 1m 37s · 19 turns · 68 in / 6,318 out tokens

With context: $0.6404 · 2m 6s · 28 turns · 75 in / 7,456 out tokens

86%

16%

Customer Enrichment Pipeline

TaskFlow API and modular DAG structure

Criteria

Without context

With context

@dag decorator

100%

@task decorator

100%

XCom via return values

100%

No heavy logic in DAG file

58%

50%

Uses {{ ds }} macro

100%

No global state

100%

Project structure: dags/__init__.py

100%

Project structure: dags/common/

Tests directory

100%

DagBag import test

100%

DAG integrity test

100%

DAG tags

100%

Without context: $1.2720 · 5m 14s · 33 turns · 79 in / 21,528 out tokens

With context: $1.9239 · 5m 56s · 52 turns · 98 in / 24,433 out tokens

90%

Vendor Report Processing Pipeline

Sensor configuration and error handling

Criteria

Without context

With context

mode='reschedule'

100%

Sensor timeout set

100%

poke_interval set

100%

Task failure callback

100%

DAG failure callback

100%

Callback logs context

100%

Cleanup trigger_rule ALL_DONE

100%

Branch join trigger_rule

No depends_on_past

100%

catchup=False

100%

DAG tags

100%

Without context: $0.7500 · 3m 2s · 33 turns · 81 in / 9,087 out tokens

With context: $1.0439 · 3m 19s · 43 turns · 294 in / 10,288 out tokens

Evaluated: 2 days ago
Agent: Claude Code

Table of Contents

Daily Transaction Ingestion Pipeline Customer Enrichment Pipeline Vendor Report Processing Pipeline

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