PROJECT MANAGEMENT

Flag mid-sprint Linear issues added after sprint start

Watches a Linear cycle and, whenever an issue is added to it after the cycle has already begun, posts a scope-creep alert to Slack with the issue's estimate, author…

CategoryProject Management
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerLinear issue added to or updated in a cycleLinearLinear
  • LogicKeep only issues added after the cycle start date
  • ActionFetch cycle's current issue count and total estimateLinearLinear
  • LogicCompute added points and % increase vs committed scope
  • OutputPost scope-creep alert to the squad Slack channelSlack

What it does

Detects when work is injected into an in-progress Linear cycle. Every time an issue is moved into the active cycle after its start date, the workflow checks whether the cycle is already underway and, if so, raises a scope-creep flag with the details the lead needs to decide whether to accept or defer it.

When to use it

Run this on any squad that commits to a fixed scope at sprint planning and wants discipline about additions. It turns silent mid-sprint adds into a visible, point-quantified signal instead of a surprise at retro.

How it works

  1. 1**Trigger** — Linear fires when an issue is added to or updated within a cycle.
  2. 2**Logic** — Compare the issue's added-at timestamp against the cycle start date; pass only issues injected after the cycle began.
  3. 3**Action** — Fetch the cycle's current scope (issue count and summed estimate) from Linear.
  4. 4**Logic** — Compute the added points and the percentage increase over the originally committed total.
  5. 5**Output** — Post a Slack alert to the squad channel naming the new issue, its estimate, who added it, and the revised cycle total.

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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