DATA OPS
Agent that triages BigQuery schema changes and files fix tickets in Linear
An agent investigates each BigQuery schema change end to end — reading lineage and query logs.
How it runs
The automated pipeline, trigger to output.
- TriggerSchema-change webhookHTTP webhook
- ActionRead column diff and dbt lineage from GitLabGitLab
- ActionPull recent query usage from AxiomAxiom
- LogicAgent classifies severity and drafts remediation plan
- OutputOpen scoped, owner-assigned Linear ticketLinear
What it does
Goes beyond listing affected models. When a BigQuery table's schema changes, an agent gathers the evidence — the column diff, the dbt models that reference it from GitLab, and recent query usage from Axiom — and reasons about real impact: which models will actually break, which are cosmetic, and what the fix likely is. It then drafts a Linear ticket with a clear remediation summary and assigns it to the owner.
When to use it
Use it when a raw blast-radius list still leaves a human to interpret severity and write up the fix. The agent does that judgment work, so your data team gets actionable, pre-scoped tickets instead of another alert to triage by hand.
How it works
- 1A webhook fires when a schema change is detected on a tracked BigQuery table.
- 2The agent reads the column diff and queries dbt lineage from GitLab.
- 3It pulls recent query usage from Axiom to gauge whether anything live depends on the change.
- 4It reasons over the evidence to classify severity and draft a remediation plan.
- 5It opens a scoped Linear ticket assigned to the resolved owner with the assessment attached.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect GitLabRepos, MRs, pipelines, registry.
- 3Connect AxiomLog streams, queries, dashboards.
- 4Connect LinearIssues, projects, cycles, triage.
- 5Connect HTTP webhookTrigger any URL on agent actions.
- 6Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 7Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 8Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Data Ops workflows
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PR-time Snowflake schema contract check on dbt model changes
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Agent-triaged warehouse drift with impact analysis and runbook update
On a webhook from your warehouse audit log, an agent investigates the changed column, traces which downstream models and dashboards depend on it.
Cross-warehouse replication schema mismatch reconciler
Compares the column shape of mirrored tables between BigQuery and Snowflake and, when a replicated table has drifted out of sync between the two, opens an Asana task for the data…
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

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