gcp-data-engineeringlisted

# GCP Data Engineering Skills Eight single-purpose skills for running a BigQuery platform. Each one is opinionated, states what it refuses to do, and produces copy-paste ready output. **These skills read your warehouse and never write to it.** Read `references/execution-model.md` before the first task in any session that touches a live project. The short version: - Connected to the BigQuery MCP server or an authenticated `bq` CLI, the skills inspect schemas and run read-only SQL for themselves. Cost findings come from real job history rather than from reading the SQL and guessing. - They never call `execute_sql`, the one read-write tool in the MCP server. Every write, backfill, IAM change, and `terraform apply` is emitted as a command for a human to run. - "Just run it" does not change that. Hand over the statement and explain why. - With no connection at all they still work, they just say plainly that the numbers are unverified. ## Routing | The user wants | Skill | | --- | --- | | A query tuned, a bill explained, partition or cluster choices | `bq-cost-auditor` | | SQLX models, staging or mart layers, assertions, incremental logic | `dataform-modeler` | | A data contract, breaking-change review, column deprecation | `bq-schema-contract` | | Terraform for datasets, service accounts, IAM, Cloud Run jobs | `terraform-gcp-scaffolder` | | An Airflow DAG, sensors, backfills, scheduling on Composer | `composer-dag-builder` | | A failed DAG, a stale table, wrong numb