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AI agent for data architects

Data Contract Violation Agent

Catch contract breaks early and confirm each fix restores the feed

MonitoringRisk managementExecutives and strategy
See how it worksGet access
Data Contract Violation Agent: what goes in, what the agent does and what you get

What it does

A source team renames a column and the sales dashboard goes blank on Monday. This agent monitors each data feed and compares its current schema, volume and freshness with the written data contract. When a field changes type, a column vanishes or volume drops sharply, it flags a violation and identifies which tables, dashboards and teams consume that feed. It opens a ticket with the producing team, with the exact difference and the affected consumers. It re-checks after the producer replies or fixes the feed. If the fix does not clear the violation, it escalates. The data owner approves any temporary workaround, such as a view that maps the old name. Edge case: a planned change with notice is logged as expected, not as a violation.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Scheduled check runs 2 USES A TOOL Read current schema, volume and freshness of eachfeed 3 USES A TOOL Compare with the data contract and the plannedchange calendar 4 CHECKS THE RESULT Does the feed match the contract? If not: Log a violation and identify affected consumersfrom lineage. Back to step 2. 5 DOES Draft a ticket with the exact difference and impact 6 YOU APPROVE Data owner approves the ticket and any workaround 7 USES A TOOL Open the ticket with the producing team 8 USES A TOOL Rerun the check after the next load 9 CHECKS THE RESULT Is the violation cleared? If not: Escalate to the producer's manager and keep theworkaround in place. Back to step 8. 10 RESULT Closed violation and updated contract log
Read the steps as a list
  1. Scheduled check runs
  2. Read current schema, volume and freshness of each feed
  3. Compare with the data contract and the planned change calendar
  4. Does the feed match the contract?If not: Log a violation and identify affected consumers from lineage. Back to step 2.
  5. Draft a ticket with the exact difference and impact
  6. Data owner approves the ticket and any workaroundThe agent waits here for your OK.
  7. Open the ticket with the producing team
  8. Rerun the check after the next load
  9. Is the violation cleared?If not: Escalate to the producer's manager and keep the workaround in place. Back to step 8.
  10. Closed violation and updated contract log

How it decides

It flags schema changes, null spikes above 5 percent and volume swings above 30 percent. It marks a violation fixed only when the next load matches the contract.

  • Flag any removed or retyped column
  • Flag null rates above 5 percent versus baseline
  • Flag volume swings above 30 percent day over day
  • Treat changes on the planned calendar as expected

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Null and volume thresholds (default 5 percent and 30 percent)
  • Check frequency (default hourly and daily)
  • Escalation time (default 48 hours)
  • Ticket destination (default the data team's queue)

What keeps you in control

It always asks you first

  • Data owner approves tickets and temporary workarounds

Hard limits

  • Never change a production feed without owner approval
  • Never silence a violation
  • Log every change

It stops when

  • Done: Feed matches the contract again
  • Stop: Producer cannot fix within the agreed time, so hand to the data owner

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensAt 6:00 the orders feed drops column cust_region. The agent lists 4 dashboards and 2 models that use it and opens a ticket. The next load is still missing the column, so the check fails. It escalates and the data owner approves a view that maps the field. Two days later the producer restores the column and the check passes.

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