Engineering Data Pipelines Agent Skill

Data engineering knowledge reference covering Airflow, Dagster, Kafka Streams, Flink, dbt, and data quality patterns. Use when building data pipelines, ETL workflows, stream processing, or data quality checks.

793 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

238

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/telagod/code-abyss --skill engineering-data-pipelines

The instruction itself

1 sections, as written by the author

数据工程域 · Data Engineering

> 判断先于执行：决定「是否做 / 选什么 / 如何取舍」（栈、方案、架构、权衡）前，先读领域判断内核 skills/_kernel/backend/SKILL.md——它管 judgment，本秘典管 execution；冲突时以内核判断为准。

编排：Airflow(调度) | Dagster(资产) | Prefect(现代流)
流处理：Kafka Streams(嵌入式) | Flink(集群) | Spark Streaming
质量：Great Expectations | dbt tests | Soda Core

编排检查项

幂等(UPSERT/分区覆盖) | 增量(WHERE updated_at > last_run) | 事件驱动触发 | 跨 DAG 依赖 | 数据血缘(ref()/Asset deps)

流处理检查项

质量检查项

分层验证(源→转换→目标) | 完整性+准确性+一致性 | 及时性阈值 | 加权评分 | 告警(Slack/PagerDuty)

工具对比、API 用法、质量维度详见 references/details.md

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17k tokens

How to use it

Copy the folder

Take telagod/engineering-data-pipelines from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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