PROJECT MANAGEMENT

Attribute GitHub PRs opened against a milestone after it was frozen

When a pull request is added to a GitHub milestone after that milestone's planned freeze date, this workflow records the PR, its size, and the author or linked requester…

CategoryProject Management
Enginesim
Difficultyadvanced
Triggerwebhook
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerGitHub PR assigned to milestoneGitHubGitHub
  • LogicAssigned after milestone freeze date?
  • ActionRead diff size and resolve requesterGitHubGitHub
  • LogicBucket PR size into S/M/L
  • ActionAppend PR to Airtable scope ledgerAirtableAirtable
  • OutputAlert engineering lead in SlackSlack

What it does

For teams that plan by GitHub milestones, this catches PRs slotted into a milestone after the freeze date, estimates their size from the diff, attributes them to the author or the requester named in the linked issue, and logs them while alerting the lead.

When to use it

Use it when your delivery boundary is a GitHub milestone rather than a Linear cycle, and out-of-plan PRs keep appearing late. It gives engineering managers a defensible record of unplanned work and who asked for it.

How it works

  1. 1A GitHub webhook fires when a PR is assigned to a milestone.
  2. 2A logic step compares the assignment time to the milestone's stored freeze date and ignores PRs added before it.
  3. 3An action pulls the PR's changed-lines count as a size proxy and resolves the requester from the linked issue or PR author.
  4. 4A logic step classifies size into S/M/L buckets for the ledger.
  5. 5An action appends the PR, size bucket, and attributed stakeholder to an Airtable scope ledger.
  6. 6An output posts a short alert to the engineering lead's Slack so the addition is acknowledged in real time.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect AirtableBases, tables, views, automations.
  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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