DEVOPS

File Linear cleanup tickets for stale 100% flags with owners

Detects flags pinned at 100% for 30+ days and creates a Linear issue per flag, auto-assigned to the team that last touched it, with a removal checklist.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule triggers the run
  • ActionRead flag rollout state from DatadogDatadogDatadog
  • LogicFilter to flags at 100% for 30+ days
  • ActionInfer owning team from GitHub commit historyGitHubGitHub
  • LogicSkip flags that already have an open issue
  • OutputCreate assigned Linear cleanup issueLinearLinear

What it does

This workflow turns stale feature flags into owned, trackable cleanup work. It finds every flag that has been serving 100% for at least 30 days, figures out which team owns it from recent commit history, and files a Linear issue with a standard removal checklist so the debt lands on a real backlog with an accountable owner.

When to use it

Use it when flag cleanup keeps slipping because nobody owns it. Instead of opening code changes directly, this routes the work into your existing planning flow, letting teams schedule removals into a sprint and attach context.

How it works

A weekly schedule triggers the run. The workflow reads flag rollout state and last-change timestamps from Datadog, then filters to flags at 100% for 30+ days. For each stale flag it queries GitHub for the most recent author and team on the flag's references to infer an owner. It creates a Linear issue titled for the flag, assigns it to the inferred team, attaches a removal checklist and the metrics snapshot, and labels it flag-debt. Finally it skips any flag that already has an open Linear issue so reruns never duplicate tickets.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DatadogMetrics, traces, log search.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  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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