PROJECT MANAGEMENT

Block Asana task assignment when assignee is over sprint capacity

Watches for new task assignments in an Asana sprint project, forecasts the assignee's committed hours against their capacity.

CategoryProject Management
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerAsana task assigned in sprint projectAsanaAsana
  • ActionFetch assignee's open sprint tasks and effort estimatesAsanaAsana
  • LogicSum committed hours vs. capacity threshold
  • ActionUnassign task and post overcommit commentAsanaAsana
  • OutputDM assigner the overage and remaining headroomSlack

What it does

When a task is assigned to someone in an active Asana sprint, this workflow checks whether that person already has enough committed work to fill their sprint capacity. If the new task tips them over, it removes the assignment, adds a clear comment explaining why, and notifies the assigner so the work can be re-routed before it silently slips.

When to use it

Run this on any team that plans sprints in Asana and keeps overloading the same few people. It turns capacity from a number nobody checks into a hard guardrail enforced at the moment of assignment.

How it works

  1. 1An Asana webhook fires when a task gains an assignee inside the sprint project.
  2. 2The workflow pulls all of that assignee's open tasks in the sprint and sums their estimated hours from the effort custom field.
  3. 3It compares the projected total (existing plus the new task) against the assignee's per-sprint capacity.
  4. 4A branch decides: under capacity, leave it; over capacity, continue.
  5. 5For overcommit, it clears the assignee field and posts an Asana comment naming the overage.
  6. 6It sends the assigner a Slack DM with the task link and remaining headroom so they can reassign.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AsanaTasks, projects, milestones — everywhere.
  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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