luanmorenommaciel/agentspec/data-engineering-guide

Claude Code and agent skill by luanmorenommaciel/agentspec

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Data engineering expertise for pipelines, schemas, data quality, SQL, lakehouse, and streaming. Use PROACTIVELY when the user discusses data pipelines, ETL/ELT, schema design, dimensional modeling, data quality checks, SQL optimization, dbt models, Spark jobs, Airflow DAGs, streaming pipelines, lakehouse architecture, or data contracts.

Install

npx vskill@latest install luanmorenommaciel/agentspec/data-engineering-guide

SKILL.md

Data Engineering Guide

You have access to 23 specialized knowledge base domains and 15+ data engineering agents. Route the user to the right tool based on their task.

Quick Routing

User TaskCommandAgent
Design a data pipeline / DAG/agentspec:pipelinepipeline-architect
Design a schema / star schema / data model/agentspec:schemaschema-designer
Add data quality checks/agentspec:data-qualitydata-quality-analyst
Review SQL performance/agentspec:sql-reviewsql-optimizer
Choose table format (Iceberg/Delta)/agentspec:lakehouselakehouse-architect
Build RAG / embedding pipeline/agentspec:ai-pipelineai-data-engineer
Create a data contract/agentspec:data-contractdata-contracts-engineer
Migrate legacy ETL/agentspec:migratedbt-specialist + spark-engineer

Knowledge Domains Available

CategoryDomains
Core DEdbt, spark, airflow, streaming, sql-patterns
Data Designdata-modeling, data-quality, medallion
Infrastructurelakehouse, cloud-platforms, aws, gcp, microsoft-fabric, lakeflow, terraform
AI & Modernai-data-engineering, genai, prompt-engineering, modern-stack
Foundationspydantic, python, testing

How Agents Use Knowledge

  1. Agent reads KB index at ${CLAUDE_PLUGIN_ROOT}/kb/{domain}/index.md
  2. Loads specific pattern/concept file matching the task
  3. Falls back to MCP if KB insufficient (max 3 MCP calls)
  4. Calculates confidence from evidence matrix

When to Suggest Commands

  • User mentions "dbt model" or "staging model" → /agentspec:schema or delegate to dbt-specialist
  • User mentions "pipeline" or "DAG" or "orchestration" → /agentspec:pipeline
  • User mentions "data quality" or "expectations" or "tests" → /agentspec:data-quality
  • User mentions "slow query" or "optimize SQL" → /agentspec:sql-review
  • User mentions "Iceberg" or "Delta Lake" or "table format" → /agentspec:lakehouse
  • User mentions "RAG" or "embeddings" or "vector" → /agentspec:ai-pipeline
  • User mentions "contract" or "SLA" or "schema governance" → /agentspec:data-contract
  • User mentions "migrate" or "legacy" or "SSIS" or "Informatica" → /agentspec:migrate

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
184
Repository forks
91
7-day trend score
26

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 20 May 2026, 5 months ago.

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