PROJECT MANAGEMENT

Cross-Team Capacity Rebalance Advisor

On request, an agent reviews every team's committed Linear load against PTO-adjusted capacity and BigQuery velocity history.

CategoryProject Management
Enginepaperclip
Difficultyadvanced
Triggermanual
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerManual on-demand run
  • ActionGather committed points and assignees per teamLinearLinear
  • ActionRead PTO and holidays for planning windowGoogle CalendarGoogle Calendar
  • ActionQuery recent velocity history per teamGoogle BigQueryBigQuery
  • LogicReason over load, capacity, and history to find imbalances
  • OutputPost rebalancing plan with rationale to SlackSlack

What it does

Gives a planning lead an analyst-grade rebalancing recommendation across all squads. An agent reads each team's committed Linear scope, subtracts PTO from the shared calendar, pulls recent velocity trends from BigQuery, and reasons about where slack and strain exist. It then drafts a concrete plan: which teams are overloaded, which have headroom, and specific work it suggests moving.

When to use it

Use this before a planning meeting when you need more than a red/green flag. It is for the judgment call of who should help whom, grounded in real commitments, time off, and historical throughput.

How it works

  1. 1A manual run kicks off the agent on demand.
  2. 2The agent gathers committed points and assignees per team from Linear.
  3. 3It reads PTO and holidays from the shared Google Calendar for the planning window.
  4. 4It queries BigQuery for each team's recent velocity to calibrate realistic throughput.
  5. 5The agent reasons over load, capacity, and history to identify imbalances and candidate work to move.
  6. 6It posts a written rebalancing plan with rationale to a Slack planning channel for the lead to approve.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LinearIssues, projects, cycles, triage.
  2. 2
    Connect Google CalendarEvents, attendees, availability.
  3. 3
    Connect BigQueryDatasets, queries, schemas.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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