PROJECT MANAGEMENT

Linear sprint capacity guard against rolling velocity

When a Linear cycle starts, sums the committed story points and compares them to the team's rolling 3-cycle average velocity, posting a Slack warning if the plan is overcommitted.

CategoryProject Management
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerLinear cycle startedLinearLinear
  • ActionSum committed story points in cycleLinearLinear
  • ActionFetch last 3 cycles' completed pointsLinearLinear
  • LogicCommitment exceeds rolling velocity + buffer?
  • OutputPost overcommitment warning to SlackSlack

What it does

This workflow watches Linear for the start of a new cycle, then checks whether the team has bitten off more than its recent history says it can chew. It pulls the total estimate of every issue assigned to the new cycle and compares that against the average completed points across the last three cycles. If the commitment exceeds rolling velocity by a configurable margin, it raises a clear, actionable alert in Slack so the team can rescope before work begins.

When to use it

Use it when your team plans in Linear cycles and repeatedly carries unfinished work into the next sprint. It catches overcommitment on day one instead of at the mid-sprint check-in, giving leads time to defer scope while it is still cheap.

How it works

  1. 1A Linear webhook fires when a new cycle becomes active.
  2. 2The flow fetches all issues in the cycle and sums their estimates.
  3. 3It queries the last three completed cycles and computes average delivered points.
  4. 4A logic step compares committed points to velocity plus the buffer margin.
  5. 5If over the threshold, a Slack message names the team, the gap, and the suggested issues to cut.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LinearIssues, projects, cycles, triage.
  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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