HR & RECRUITING

On-Demand Candidate Decision Packet for Approval

A recruiter triggers this agent for a candidate and it autonomously gathers all interview artifacts, drafts a balanced decision packet with bias checks, files it in Confluence.

CategoryHR & Recruiting
Enginepaperclip
Difficultyadvanced
Triggermanual
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerRecruiter requests decision packet
  • ActionRetrieve all interview feedbackNotionNotion
  • ActionDraft balanced packet with bias reviewOpenAI
  • LogicVerify all required interviewers submitted
  • ActionPublish packet to ConfluenceConfluenceConfluence
  • OutputOpen committee approval taskAsanaAsana

What it does

On request, an agent assembles a complete candidate decision packet: every interviewer's feedback, the resume context, competency consensus, dissenting views, and a documented bias review. It files the packet and opens a formal approval task so the hiring committee can sign off with a full record.

When to use it

Use it for senior or sensitive hires where you need a thorough, auditable packet rather than a quick channel post. Good when the recruiter wants to kick off packet assembly manually once they judge the loop is genuinely ready.

How it works

  1. 1A recruiter manually triggers the workflow with a candidate identifier.
  2. 2The agent retrieves all interviewer feedback and ratings from the Notion hiring database.
  3. 3It uses OpenAI to draft a balanced decision packet, surfacing both consensus and disagreement and running a bias-language review with flags.
  4. 4A logic step verifies every required interviewer has submitted before proceeding, otherwise it requests the missing ones.
  5. 5The completed packet is published as a Confluence page in the hiring space.
  6. 6An approval task is opened in Asana for the hiring committee, linking the packet and assigning the decision owner.

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 ConfluenceSpaces, pages, blueprints.
  4. 4
    Connect AsanaTasks, projects, milestones — everywhere.
  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.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.