A curated collection of Agent Skills for working with Masthead Data — BigQuery data observability and cost optimization for Google Cloud.
Before installing, make sure you have:
- A Masthead Data account with a provisioned insights dataset. Request access →
gcloudCLI authenticated (gcloud auth login)bqCLI available (bq versionto verify)- BigQuery permissions: ability to run jobs and read data in your project
When a skill runs for the first time it will ask you for your Masthead insights dataset ID (e.g. my-project.masthead_insights). It stores this in your project's instructions file so you won't be prompted again.
These skills are designed to be consumed directly by AI agents such as Claude Code or GitHub Copilot.
Add the Masthead plugin to your Claude Code tools configuration (about Claude Code plugins):
/plugin marketplace add masthead-data/for-agents
/plugin install masthead-data-skills@masthead-data
/reload-plugins
Use the Vercel Skills CLI to install skills directly into your project:
# Install all skills globally (available in all projects)
npx skills add masthead-data/for-agents --global
# Install a specific skill
npx skills add masthead-data/for-agents --skill masthead-storage-savings-with-tablesOnce installed, ask your agent naturally:
Optimize my BigQuery storage costs using Masthead insights
Optimize BigQuery compute costs by assigning Dataform, dbt, or Airflow models to slot reservations or on-demand compute.
What you get: updated reservation assignment config for your orchestration tool (Dataform, dbt or Airflow), verified against live Masthead recommendations.
Optimize BigQuery storage costs by identifying and removing dead-end and unused tables.
What you get: a reviewed CSV of waste candidates ranked by savings impact, and a ready-to-run shell script to drop approved tables.
Optimize BigQuery storage costs at the dataset level by switching storage billing models and setting expiration policies.
What you get: a prioritized list of datasets eligible for billing model changes or expiration policies, and ready-to-run commands to apply them.