ENGINEERING
Daily PR review-latency leaderboard to engineering channel
Each morning it computes per-PR and per-reviewer wait times from GitHub, stores a daily snapshot in Postgres for trend tracking.
How it runs
The automated pipeline, trigger to output.
- TriggerMorning schedule triggers the daily run
- ActionPull open PRs and review events from GitHubGitHub
- LogicCompute wait time per PR and backlog per reviewer
- ActionWrite a dated latency snapshot to PostgresPostgres
- OutputPost the ranked latency leaderboard to SlackSlack
What it does
Gives the whole team a single daily picture of where review time is going. It ranks currently open PRs by how long they've been waiting on review and surfaces which reviewers have the deepest backlog, while quietly logging the numbers so you can watch the trend over weeks.
When to use it
When you want visibility and a shared norm around review speed without micromanaging. Useful for eng leads running weekly retros who need real latency data rather than gut feel.
How it works
- 1A morning schedule triggers the run.
- 2The flow pulls all open PRs and their review-request and review-submission events from GitHub.
- 3A logic step computes time-waiting per PR and aggregates backlog per reviewer.
- 4It writes a dated snapshot row into Postgres so historical trends accumulate.
- 5It formats a leaderboard of the slowest open PRs and the most-backlogged reviewers.
- 6It posts that digest to the engineering Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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