DATA OPS
Investigate a Schema Break and Draft a Remediation Plan in Linear
On demand, an agent investigates a reported Snowflake schema break, traces the full chain of affected dbt models and dashboards, drafts a step-by-step remediation plan.
How it runs
The automated pipeline, trigger to output.
- TriggerOperator manually starts investigation for a table
- ActionQuery Snowflake to confirm and characterize the changeSnowflake
- LogicTrace dbt and dashboard dependency blast radius
- LogicReason through ordered remediation steps and owners
- OutputFile remediation plan as an assigned Linear ticketLinear
What it does
When a schema break is reported, an agent does the legwork: it inspects the changed Snowflake table, walks the dependency chain to every affected dbt model and the dashboards downstream of them, and writes a concrete remediation plan. It then files that plan as a structured Linear ticket assigned to the right owner.
When to use it
Use it for the messy, judgment-heavy breaks where you need analysis, not just an alert — understanding blast radius, sequencing fixes, and deciding who does what. Best when triggered manually after a drift alert lands and someone needs a plan fast.
How it works
- 1An operator manually triggers the investigation with the broken table name.
- 2The agent queries Snowflake to confirm the current schema and characterize the change.
- 3It traces the dependency graph across dbt models and downstream dashboards to scope the blast radius.
- 4It reasons through a remediation sequence — which models to patch, in what order, and who owns each.
- 5It files a detailed Linear ticket with the plan, impact summary, and an assignee.
Set it up
What you configure once, before turning it on.
- 1Connect SnowflakeWarehouses, queries, shares.
- 2Connect LinearIssues, projects, cycles, triage.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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