# masthead-compute-savings-with-workload-assignments

> Claude/Codex skill by [@masthead-data](https://omgskills.com/library/masthead-data/index.md) · 0 stars · Updated 2026-10-22

Optimize BigQuery compute costs by reassigning data models (Dataform, dbt, Airflow) or principals (service accounts, users) to slot reservations or on-demand compute based on Masthead recommendations without impacting performance.

Tags: agent-skills, ai-agents, bigquery, cost-optimization, finops, masthead

## Install

```sh
git clone https://github.com/masthead-data/for-agents /tmp/for-agents && ln -s /tmp/for-agents/skills/masthead-compute-savings-with-workload-assignments ~/.claude/skills/masthead-compute-savings-with-workload-assignments
```

## From README

Optimize BigQuery Compute Costs (Models & Principals) Purpose Automatically translate Masthead compute-cost recommendations (views.insight / exported insights tables) into concrete, verified configurations for BigQuery reservations and orchestration pipelines. The primary objective is reliable enterprise workload cost optimization without performance impact. Workloads are systematically routed between autoscale slot reservations and on-demand compute pools based on simulated execution profiles. Workload Scope Masthead evaluates two classes of compute recommendations: Data Models (DAGMODEL): Orchestrated pipeline nodes across Dataform actions, dbt models, and Airflow tasks. Principals (PRINCIPAL): Identity-based workloads executed by service accounts or users across projects.

## Links

- HTML page: https://omgskills.com/library/masthead-data/for-agents/skills/masthead-compute-savings-with-workload-assignments/
- GitHub: https://github.com/masthead-data/for-agents
- Author: [@masthead-data](https://omgskills.com/library/masthead-data/index.md)

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