PERSONAL PRODUCTIVITY

Weekly OKR Nudge with Drafted Progress from Asana

Every Friday it reads each OKR owner's Asana task completion and DMs them a pre-written progress update on Slack to confirm or edit before the weekly review.

CategoryPersonal Productivity
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFriday morning schedule fires
  • ActionRead tracked OKR project tasks from AsanaAsanaAsana
  • LogicCompute KR percent-complete and flag stalled KRs
  • ActionDraft owner-voiced progress text per KROpenAI
  • ActionResolve each owner's Slack user IDSlack
  • OutputDM each owner their editable progress draftSlack

What it does

It removes the blank-page problem from weekly OKR check-ins. The workflow reads task completion data from each owner's Asana project, calculates a percent-complete signal per key result, and sends each owner a Slack DM containing a ready-to-edit draft of their progress update. Owners reply with a confirm or a tweak instead of writing from scratch.

When to use it

Use it when your team tracks key results as Asana projects or sections and runs a recurring Friday OKR review. It is ideal for teams where updates are chronically late because writing them is friction, not because progress is missing.

How it works

  1. 1A Friday-morning schedule fires the run.
  2. 2It pulls each tracked Asana project's tasks, including completed counts and due dates.
  3. 3A logic step computes percent complete per key result and flags any KR with zero movement in the last 7 days.
  4. 4An OpenAI step drafts a short, owner-voiced progress sentence per KR from the numbers.
  5. 5It looks up each owner's Slack user ID.
  6. 6It DMs every owner their personalized draft with confirm and edit prompts.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AsanaTasks, projects, milestones — everywhere.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    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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