ATS sits alone in Greenhouse.
Judging candidate screening also takes assess qualifications, and that never shares a screen with Greenhouse.
People ops teams run hiring decisions on stale, scattered data: Ashby and Greenhouse each hold a piece, none hold the whole. Manual screening takes 20+ minutes per resume.
The hiring decision pays for it.
Judging candidate screening also takes assess qualifications, and that never shares a screen with Greenhouse.
Assess qualifications lives in Ashby, cut off from ats, so candidate screening guesses at the link.
Rank candidates lands in Ashby hours early. Too far from Greenhouse to change the hiring decision in time.
Under The Hood
ATS
Assessment Platforms
One worklist: Parse resumes, assess qualifications, rank candidates, identify red flags, recommend next steps. Ranked by priority, top risks flagged, a next step on each.
The Context Store
Ashby and Greenhouse get reconciled up front for candidate screening: ATS, Assessment Platforms, Background Check Services, Communication Tools mapped to a single role view instead of 2 separate APIs.
Your agent queries one surface instead of three APIs. Faster responses, lower cost per query, and results that work because the relationships were built before you asked the question.
The Prompt
Two steps. Your data, your results, under 60 seconds.
Help me turn Greenhouse and Ashby into a single hiring decision I can act on.
SETUP
The Agent MCP is connected to 2+ systems; query them directly, no API code.
WORKFLOW
list connectors -> link Greenhouse and Ashby -> pull ATS, Assessment Platforms, Background Check Services, Communication Tools -> join on the role key -> analyze. An unlinked tool returns a self-describing prompt; a one-time browser auth and retry.
TASK
Parse resumes, assess qualifications, rank candidates, identify red flags, recommend next steps, then give me a single worklist: sorted by what needs me first, each line with the why and the move.The Outcome
10x
~10x. Candidate screening drops from a 2-hour chore to one query.
90%
90% less spend: no glue code; it runs on your existing 2-tool stack to parse resumes.
2 -> 1
2 -> 1: candidate screening answers Greenhouse and Ashby in a single query.
Based on internal benchmarks comparing Context Store queries to sequential API calls across equivalent datasets.
01 · Output
A 1-10 score on each role means the urgent ATS rises to the top of candidate screening on its own.
02 · Signal
When your applicant tracker and Greenhouse disagree on parse resumes, the gap is flagged. Not averaged into a guess.
03 · Context
Assess qualifications from Ashby sits beside each item, letting you parse resumes without switching tabs.
04 · Action
Candidate Screening closes each role with a recommendation. Who to contact and what to send. Ready to run.
05 · Brief
The worklist arrives meeting-ready: ATS first, sources attached, Greenhouse and Ashby reconciled.
Your hiring decision is only as fresh as the slowest tab. Manual distribution wastes time. Yet the inputs sit split across Stripe + Shopify + Salesforce.
People ops teams run hiring decisions on stale, scattered data: LinkedIn Ads / Salesforce / Greenhouse each hold a piece, none hold the whole. Top candidates are off market in 10 days.
The data for your hiring decision already exists in Confluence + Notion. The problem is no one view joins it. VIP users require priority response.
Didn't find your answer? Please don't hesitate to reach out.
Can Candidate Screening run on a schedule?
What Greenhouse data does Candidate Screening touch?
How fresh is the role data Candidate Screening uses?
How do I build a candidate screening agent with Greenhouse and Ashby?
47+ connectors including Greenhouse and Ashby are ready. Give candidate screening the access to parse resumes.