Agent context
Google Search Console models
4 SQL models that turn the raw Google Search Console tables into the reports people ask about. Deploy them in Weld and your agent queries the definitions behind every number.
How the set is built
- 4Raw tables
- 4Staging
- 4Core
- 4Analytics
Staging cleans each raw table once, core holds the logic, and analytics is the table dashboards and agents read.
- Page performance dailyThe Pages tab of the Performance report, by day.grain: date_day x site x page · 1 raw table
- Query page monthlyWhich pages rank for which query, per month, and how a query's clicks split across your pages. The usual way to spot two pages competing for one query.grain: month x site x query x page · 1 raw table
- Query performance dailyThe Queries tab of the Performance report, by day.grain: date_day x site x query · 1 raw table
- Site performance dailyThe Search Console Performance report headline: clicks, impressions, CTR and average position per site per day, plus how much of it the query tables cannot see.grain: date_day x site · 2 raw tables
- Weld or dbt
- The same SQL in both dialects. Sync the folder with GitHub Sync, or copy the dbt models into your project.
- Check before you rely on it
- Reconcile a month against Google Search Console's own reports first. Each model's notes say what the synced data can and can't support.
Connect Google Search Console.
Your agents start with context.
Sync Google Search Console to your warehouse, deploy these models, and query them from Claude, Cursor or ChatGPT over MCP. Free for 14 days, no credit card.