95 tagged airflow, measured the same way as everything else here.
Browse within: bigquery 38data-engineering 38awesome-list 37workflow 14python 11scheduler 10apache 9apache-airflow 9ETL 5Orchestration 5scheduling 5
Skill Claude CodeCodex
Adopt and maintain the apache-magpie framework in a project repo via the snapshot-based adoption mechanism. The only framework skill committed in an adopter's repo; every other skill is a symlink the adopt sub-action wires up. Sub-actions: /magpie-setup - first-time adoption (default; main-checkout only) /magpie-setup…
Skill Claude CodeCodex
Replace the manual commit-by-commit classification step in breeze release-management prepare-provider-documentation with AI-driven classification. For each provider with pending changes, analyze every PR (batched into one sub-agent per provider, not one per PR), pay special attention to potentially breaking changes by…
Skill Claude CodeCodex
Upgrade the pinned Flask-AppBuilder (FAB) dependency in the Apache Airflow FAB provider (providers/fab/). Bumps the exact flask-appbuilder== pin and its mirror constant, regenerates uv.lock, drives the testfabalignment.py drift tripwire, reviews the vendored security-manager override.py against the new upstream FAB…
Skill Claude CodeCodex
Builds Airflow 3.1+ plugins that embed FastAPI apps, custom UI pages, React components, middleware, macros, and operator links directly into the Airflow UI. Use when building anything custom inside Airflow 3.1+ that involves Python and a browser-facing interface - creating an Airflow plugin, adding a custom UI page or…
Skill Claude CodeCodex
Persists task and asset state across retries and DAG runs using Airflow 3.3's AIP-103 key/value stores (taskstatestore, assetstatestore) and the crash-safe ResumableJobMixin. Use when the user asks about task state store, checkpointing in tasks, persisting state across retries, job IDs surviving worker crashes…
Skill Claude CodeCodex
Define reusable Airflow task group templates with Pydantic validation and compose DAGs from YAML. Use when creating blueprint templates, composing DAGs from YAML, validating configurations, or enabling no-code DAG authoring for non-engineers.
Skill Claude CodeCodex
Operate and maintain this repository's Shenzhen tennis alert platform across Apache Airflow 3, the Cloudflare Worker and D1 web subscription service, Tencent SES email, and the Android-host WeChat sender. Use for problem diagnosis, incident response, production health checks, DAG or notification failures…
Skill Claude CodeCodex
Expert-level Apache Airflow orchestration, DAGs, operators, sensors, XComs, task dependencies, and scheduling.
Skill Claude CodeCodex
A set of on-demand project reference documents for an AI coding assistant. It covers the project design, coding rules, validation checks, and agent development.
Skill Claude CodeCodex
Airflow adapter pattern for v2/v3 API compatibility.
Unknown-333/awesome-data-engineering-skills
Skill Claude CodeCodex
Write production-grade Apache Airflow DAGs using the TaskFlow API — idempotent tasks, correct scheduling and catchup, retries/SLAs, connections/variables, and avoiding top-level code. Use when creating or reviewing Airflow DAGs, scheduling pipelines, wiring task dependencies, configuring retries/backfills, or fixing…
Unknown-333/awesome-data-engineering-skills
Skill Claude CodeCodex
Build Dagster pipelines using software-defined assets — asset dependencies, partitions, resources and IO managers, asset checks, and schedules/sensors. Use when creating Dagster assets or jobs, modeling data as assets, adding partitions or backfills, wiring resources/IO managers, or migrating from task-based…
Unknown-333/awesome-data-engineering-skills
Skill Claude CodeCodex
Protect personally identifiable information in data pipelines — classifying PII, choosing masking vs tokenization vs hashing vs encryption, dynamic data masking and column-level access control, and handling deletion/right-to-be-forgotten. Use when handling sensitive data, masking or anonymizing PII, meeting…
Skill Claude CodeCodex
Agentic data quality validation across warehouses (DuckDB, BigQuery, Athena, Databricks, Postgres) with LLM diagnosis, root cause analysis, and audit trail.