ENGINEERING

Stale Feature-Flag Cleanup PR After 100% Rollout

Watches your flag-management Postgres table for flags that have sat at 100% rollout past a grace window.

CategoryEngineering
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule fires
  • ActionQuery Postgres for flags past grace window at 100%PostgreSQLPostgres
  • ActionSearch repo for all references to each flag keyGitHubGitHub
  • ActionRewrite files to remove flag and keep live pathOpenAI
  • ActionOpen draft cleanup PR per flagGitHubGitHub
  • OutputPost PR links to engineering SlackSlack

What it does

Finds feature flags that finished rolling out and have been fully enabled long enough to be considered permanent, then drafts the cleanup PR a human would otherwise write by hand. The outcome is a ready-to-review branch that removes the flag check and collapses the kept code path.

When to use it

Run it nightly when your team ships behind flags and tends to leave them in the code months after the rollout is done. Best for codebases where flag checks follow a consistent pattern an LLM can rewrite reliably.

How it works

  1. 1A nightly schedule fires the workflow.
  2. 2Query Postgres for flags at 100% rollout whose `fully_enabled_at` is older than the grace window (e.g. 30 days).
  3. 3For each candidate, search the GitHub repo for every reference to the flag key.
  4. 4Send the matched code spans to OpenAI to rewrite each file with the flag removed and the live branch kept.
  5. 5Open a draft PR per flag with the rewritten files and a checklist of touched call sites.
  6. 6Post the PR link to the engineering Slack channel for an owner to claim.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.