Codility and Greenhouse integration: automate coding tests, capture scores, and standardize screening

This article explains how the Codility integration for Greenhouse connects code assessment workflows to applicant tracking data, and why teams use it to improve engineering hires. It covers the integration's capabilities, typical users, implementation steps, measurable benefits, and practical best practices. Read on for a concise, actionable guide you can use to evaluate whether linking Codility to Greenhouse fits your hiring process and how to get measurable improvements in speed and screening accuracy.

At-a-glance: What the Codility–Greenhouse integration does

• Automates invitation and result flow Creates and sends Codility tests from Greenhouse, then captures scores and reports back into the candidate's Greenhouse profile to centralize evaluation.
• Standardizes assessment-to-stage transitions Automatically advances or tags candidates in Greenhouse based on Codility outcomes and custom rules, reducing manual stage changes.
• Preserves audit trails Records test submissions, timestamps, and candidate reports in Greenhouse for compliance and hiring analytics.
• Supports role-specific templates Maps job profiles in Greenhouse to task templates in Codility so each role receives consistent, job-relevant tests.
• Integrates scoring metadata Pushes granular metrics (e.g., coding correctness, performance, plagiarism flags) into custom fields or scorecards.

The integration is designed to remove manual work between screening and assessment tools while keeping evaluation data centralized in the ATS. That streamlines recruiter workflows and provides hiring managers with faster, consistent evidence for decision-making.

Who should consider this integration

• High-volume engineering hiring teams Teams that run many technical screens and need consistent, repeatable evaluation across candidates and roles.
• Distributed or remote interview teams Organizations that rely on asynchronous assessments to triage candidates across time zones before live interviews.
• Hiring managers seeking objective evidence Managers who prefer skills-based signals integrated into the ATS alongside resumes and interview notes.
• Teams tracking hiring metrics Groups that need assessment data in Greenhouse to report on funnel conversion, quality-of-hire, and time-to-hire.

Key benefits (practical outcomes)

• Faster screening Reduces recruiter time spent sending tests and collecting results — shortens the time between application and decision by automating steps.
• Improved evaluation consistency Enforces role-specific tasks and scoring rubrics so candidates for the same role are evaluated with the same criteria.
• Lower risk of mis-hires Provides job-relevant evidence that complements interviews, decreasing reliance on resume impressions alone.
• Centralized reporting Combines assessment metrics with ATS data for clearer analytics on candidate quality and funnel efficiency.
• Better candidate experience Automated scheduling, clear instructions, and timely status updates reduce friction during the technical screening phase.

Typical integration mapping between Greenhouse and Codility

Technical setup is typically straightforward: enable the Codility integration in Greenhouse, configure API keys, map tests to job templates, and set up automation rules for stage changes and scorecard updates. A small pilot with one or two roles helps validate mappings before scaling company-wide.

Practical setup checklist

• Permissions and API access Generate Codility API token and ensure Greenhouse user has appropriate permissions to install harvest or assessment integrations.
• Test templates Create or select Codility tasks tailored to role seniority and tech stack; avoid generic or brain-teaser problems.
• Greenhouse custom fields Create fields for Codility score, plagiarism flag, and submission timestamp to capture returned data.
• Automation rules Define clear stage transitions based on score thresholds and exception handling for incomplete tests.
• Pilot and feedback loop Run a small pilot, collect recruiter and hiring manager feedback, then iterate on test selection and pass thresholds.

Data privacy and compliance — common questions

Measuring success: KPIs to track after integration

• Time-to-first-screen Time from application to completed Codility assessment — should decrease as automation removes manual steps.
• Screen-to-interview conversion Percentage of candidates who pass assessments and move to interviews — helps validate task difficulty and cutoff thresholds.
• Interview-to-hire ratio Tracks whether assessments improve quality of interviews and reduce wasted interview cycles.
• Quality-of-hire proxy Early performance indicators (e.g., first 90-day ramp metrics, retention) for hires sourced via Codility assessments compared to baseline.

Anti-cheating and proctoring features are important for maintaining assessment validity. Codility offers plagiarism detection, environment monitoring, and task libraries designed to resist generative AI solutions. When integrated with Greenhouse, anti-cheat flags and reviewer notes are passed into the ATS to support manual review workflows.

Comparison: Manual screening vs Codility integration in Greenhouse

Common implementation pitfalls and how to avoid them

• Overly difficult or irrelevant tests Result: low candidate completion; fix by aligning tasks to job-level and tech stack.
• Unclear candidate instructions Result: higher support volume and dropouts; fix by standardizing email templates and deadlines.
• Not mapping results into hiring decisions Result: assessment data ignored; fix by adding scores to scorecards and setting transparent pass thresholds.
• Scaling too fast Result: inconsistent outcomes across roles; fix by piloting and documenting configuration before full rollout.

Implementation timelines vary by organization size and complexity. A minimal pilot (one role, two recruiters, two hiring managers) can be configured and run in 2–4 weeks. Full rollout across multiple roles, with custom mappings and automation rules, commonly takes 6–10 weeks including stakeholder training and iteration.