ENGINEERING

Auto-assign PR reviewers by changed files and load

When a pull request opens, picks the best reviewers from the touched code areas, balances against each reviewer's current open-review load.

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerPR opened or marked ready for reviewGitHubGitHub
  • ActionFetch changed file paths for the PRGitHubGitHub
  • LogicMap paths to reviewer pools and rank by open-review load
  • ActionAssign two lightest-loaded reviewersGitHubGitHub
  • OutputDM each reviewer the PR link in SlackSlack

What it does

Every new pull request gets routed to the right people automatically. The workflow reads which files the PR touches, maps those paths to owning reviewers, then weighs each candidate's current open-review backlog so nobody gets buried. It assigns the two lightest-loaded qualified reviewers on GitHub and pings them in Slack.

When to use it

Use it when CODEOWNERS alone keeps dumping reviews on the same one or two senior engineers, or when reviews stall because nobody was explicitly tagged. Good for teams of 5-40 where ownership is roughly known but load balancing is manual.

How it works

  1. 1A GitHub webhook fires when a pull request is opened or marked ready for review.
  2. 2The flow pulls the PR's changed file paths and matches them to an ownership map of code areas to reviewer pools.
  3. 3It queries each candidate's count of currently assigned open reviews and ranks them by lightest load.
  4. 4The top two qualified reviewers are assigned to the PR via the GitHub API.
  5. 5A Slack direct message notifies each assigned reviewer with the PR title, author, and a deep link.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  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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