TICKET MANAGEMENT

Notify every linked ticket when a canonical bug is fixed

When a canonical Linear bug is marked Done, it fans out the resolution to all merged duplicates, suppressed alerts, and linked customer tickets, then posts a fix summary to Slack.

CategoryTicket Management
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCanonical Linear bug marked DoneLinearLinear
  • ActionLoad all linked records from registryPostgreSQLPostgres
  • ActionClose merged duplicate issuesLinearLinear
  • ActionMark signature fixed in releasePostgreSQLPostgres
  • OutputPost fix summary to SlackSlack

What it does

Closes the loop after a fix ships. When the canonical Linear bug transitions to Done, this flow reads every record that was consolidated under it and notifies each one: closes merged duplicate issues, resolves any held alerts, and replies to affected customer tickets with the fix and release version.

When to use it

After you have been consolidating duplicates into canonical bugs and a fix lands. Use it so nobody who reported or was paged for the crash is left without a resolution, and so the cleanup is automatic rather than manual.

How it works

  1. 1A Linear webhook fires when a canonical bug moves to Done.
  2. 2The flow loads all linked records from the Postgres consolidation registry: duplicate issue IDs, suppressed incident keys, and customer ticket IDs.
  3. 3It closes each merged duplicate Linear issue with a resolved-via-canonical comment.
  4. 4It updates the registry to mark the signature as fixed in the resolving release.
  5. 5It posts a Slack summary of the defect, total occurrences, customers affected, and the shipping version.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LinearIssues, projects, cycles, triage.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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