DEVOPS

Open Removal PRs for Fully Rolled-Out Feature Flags

Weekly, scans Axiom telemetry for flags that have served 100% true for a sustained window, finds their call sites in the repo.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionQuery Axiom for 30-day flag evaluation ratesAxiom
  • ActionGrep GitHub repo for each flag's call sitesGitHubGitHub
  • LogicDrop flags younger than 14 days or in active experiments
  • ActionGenerate flag-removal diff inlining the enabled branch
  • OutputOpen a GitHub removal PR per flag with call-site listGitHubGitHub

What it does

Finds feature flags that are effectively permanent — they've evaluated to the same value (typically 100% enabled) across every environment for weeks — and opens a code-level cleanup PR that deletes the flag check and inlines the winning branch, with the full call-site list in the description.

When to use it

When rolled-out flags pile up as dead conditionals and nobody circles back to remove them. Run it on a weekly cadence so cleanup stays continuous instead of becoming an annual debt sprint.

How it works

  1. 1A weekly schedule kicks off the run.
  2. 2Query Axiom for flag-evaluation events over the trailing 30 days and keep flags that served one value 100% of the time in all environments.
  3. 3For each candidate, grep the GitHub repo to collect every call site referencing the flag key.
  4. 4Skip flags added in the last 14 days or with active variant experiments.
  5. 5Generate the diff that removes the conditional and keeps the enabled path.
  6. 6Open a GitHub PR per flag with the call-site list and telemetry summary, ready for review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AxiomLog streams, queries, dashboards.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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