PROJECT MANAGEMENT

Log mid-sprint Linear tickets to a scope-creep ledger with stakeholder attribution

Watches a Linear sprint cycle and, whenever an issue is added after the cycle started, records it in a Notion scope-creep ledger along with who added it, the point estimate.

CategoryProject Management
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerLinear issue added to active cycleLinearLinear
  • LogicKeep only issues added after cycle start date
  • ActionFetch project + stakeholder-request label from LinearLinearLinear
  • ActionAppend attributed row to Notion scope-creep ledgerNotionNotion
  • OutputReturn new ledger row URLNotionNotion

What it does

Keeps an auditable ledger of every ticket that lands in a sprint *after* the team committed to it. Each addition is captured with its estimate, the person who added it, and the stakeholder request it traces back to, so scope growth is never invisible at retro.

When to use it

Use it when your team commits to a sprint scope but tickets keep sneaking in mid-cycle and nobody can say later where they came from. Ideal for delivery leads who need defensible data on why a sprint slipped.

How it works

  1. 1A Linear webhook fires when an issue is added to the active cycle.
  2. 2A filter compares the issue's `addedToCycleAt` against the cycle start date; only issues added after commit pass.
  3. 3The flow reads the issue's parent project and any linked stakeholder request label to infer the originating requester.
  4. 4It appends a row to the Notion ledger database: title, estimate, added-by, requester, timestamp, and a link back to Linear.
  5. 5The new ledger row URL is the output, ready to surface in the sprint channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LinearIssues, projects, cycles, triage.
  2. 2
    Connect NotionPages, databases, comments.
  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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