DEVOPS

Publish a monthly feature-flag debt report to Notion

Monthly, tallies total flags, how many are past kill-date, average overdue age, and per-team breakdowns from your code and Statsig.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerMonthly schedule fires
  • ActionCollect flag refs and kill-dates from GitHubGitHubGitHub
  • ActionPull last-evaluated data from Statsig APIHTTP webhook
  • LogicCompute totals, overdue age, per-team breakdown
  • ActionCreate dated report page in NotionNotionNotion
  • OutputPost report link to SlackSlack

What it does

Gives leadership a recurring scorecard on flag hygiene. It counts every flag in the codebase, cross-checks against Statsig for last-evaluated dates, and computes the metrics that matter: open flag count, number past kill-date, average days overdue, and a per-team ranking. It then publishes a clean, dated report page to Notion.

When to use it

When you want flag debt visible in the same place as other engineering health metrics, trending month over month. Good for staff meetings and sprint planning where someone asks "is our flag debt getting better or worse?"

How it works

  1. 1A monthly schedule triggers the run.
  2. 2The flow collects all flag references and kill-dates from GitHub and pulls last-evaluated data from the Statsig API.
  3. 3A logic step computes totals, overdue counts, average age, and per-team breakdowns.
  4. 4It creates a dated report page in Notion with tables and trend notes.
  5. 5It posts the Notion link to Slack so the team sees the new report.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect HTTP webhookTrigger any URL on agent actions.
  3. 3
    Connect NotionPages, databases, comments.
  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.

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