HR & RECRUITING

Hire/No-Hire Decision Packet Assembler

Once all panelist scorecards for a candidate are in, it uses AI to consolidate them into a structured hire/no-hire packet in Notion, summarizing strengths, concerns…

CategoryHR & Recruiting
EngineSim + Paperclip
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFinal scorecard submitted for candidateNotionNotion
  • ActionFetch all panelist scorecards and ratingsNotionNotion
  • LogicConfirm interview loop is complete
  • ActionSynthesize feedback into decision packetOpenAI
  • ActionWrite formatted packet to candidate recordNotionNotion
  • OutputNotify hiring manager packet is readyMicrosoft Teams

What it does

When the last scorecard for a candidate lands, this workflow assembles every panelist's written feedback and ratings into a single decision packet. An AI step synthesizes the raw notes into themes, surfaces disagreements between interviewers, and produces a recommended hire/no-hire call with the reasoning laid out so the hiring manager can review fast.

When to use it

Use it when debrief prep eats hours of copy-pasting feedback into a doc. It turns scattered scorecards into a board-ready packet the moment the loop completes.

How it works

The workflow triggers on the scorecard-complete event for a candidate. It pulls all panelist scorecards and ratings, then a logic step verifies the loop is genuinely complete before proceeding. An OpenAI step consolidates the feedback into strengths, risks, areas of interviewer disagreement, and a recommended decision with confidence. The result is written as a formatted Notion page in the candidate's record and the hiring manager is notified that the packet is ready to review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect NotionPages, databases, comments.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect Microsoft TeamsChannels, chats, files.
  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.

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