DATA OPS
On-demand PII audit of a bucket with auto-filed Linear tickets
A chat-triggered agent audits a named bucket for PII on request, reasons about each finding's severity and owning team.
How it runs
The automated pipeline, trigger to output.
- TriggerChat request names a bucket to audit
- ActionList and fetch objects from S3 bucketAWS S3
- LogicReason about severity and owner, drop false positives
- ActionFile one triaged Linear ticket per exposureLinear
- OutputReply in chat with summary and ticket linksSlack
What it does
Lets an operator ask, in chat, for a PII audit of a specific bucket and gets back actionable, owned work items. The agent scans the objects, judges severity and likely data owner from path and content, and opens one Linear ticket per real exposure with a concrete fix recommendation.
When to use it
Use this for ad hoc investigations — a partner reports a leak, a new bucket is inherited, or compliance asks for a point-in-time check. The agent handles the judgment calls a flat pipeline can't.
How it works
- 1A chat message names the bucket to audit and starts the run.
- 2The agent lists and fetches objects from the S3 bucket.
- 3It scans each object for PII and reasons about severity and the owning team from the key path and contents.
- 4A logic step groups findings by dataset and discards false positives.
- 5For each confirmed exposure, the agent files a Linear ticket with severity, owner, and a remediation recommendation.
- 6It replies in chat with a summary and links to the filed tickets.
Set it up
What you configure once, before turning it on.
- 1Connect AWS S3Buckets, objects, signed URLs.
- 2Connect LinearIssues, projects, cycles, triage.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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