The Scoring System
Each candidate receives a score from 0 to 100:
70–100 (Highly Qualified): Meets all critical requirements and most optional ones.
60–69 (Qualified): Meets critical requirements; a strong match for the role.
40–59 (Partially Qualified): Missing one or more key requirements.
0–39 (Not Qualified): Does not match the core criteria.
⚙️ Setting Up Your Criteria
The quality of your screening results depends entirely on the clarity of your instructions.
The Intake Agent (Recommended)
The Intake Agent is a conversational tool that builds your screening prompt for you.
Provide the job description.
Answer the agent's clarifying questions.
The agent generates a structured prompt optimized for AI evaluation.
Manual Prompts
If writing your own prompt, ensure it is at least 250 characters and clearly distinguishes between:
Critical Requirements: Must-have qualifications (e.g., "Must have 5+ years of Java").
Optional Requirements: Nice-to-have skills that boost the score (e.g., "Experience with Kubernetes is a plus").
Deal-Breakers: Factors that should immediately disqualify a candidate (e.g., "No visa sponsorship available").
🛠️ Executing the Screen
You can screen candidates during the import process or as a separate manual step.
Automatic Screening
Check "Screen candidates after import" to process profiles immediately.
Auto-Inclusion: If you enable "Add qualified candidates to campaign," any profile scoring 60+ will automatically move into your outreach workflow.
Manual & Batch Screening
To evaluate candidates already in your database:
Select the desired candidates from the list.
Click "Screen Candidates."
Review or update the prompt and confirm.
Credit Usage: Screening costs 1 AI credit per successfully processed profile. Ensure you have a sufficient credit balance before starting large batches.
📊 Reviewing Evaluations
To understand why a candidate received a specific score, click on their profile and navigate to the Evaluation tab.
Requirements Check: A quick visual (✅, ❌, or ⚠️) showing which criteria were met.
Skills Assessment: An analysis of technical proficiency and experience levels found in the profile.
AI Notes: A summary explaining the rationale behind the score, highlighting both strengths and potential red flags.
🔄 Refining Results
If the scores aren't hitting the mark, you may need to recalibrate:
Scores too low? Your criteria might be too restrictive. Try converting some "Critical" requirements into "Optional" ones.
Scores too high? Your prompt may be too broad. Add specific year requirements or niche skill sets to increase the difficulty.
Re-screening: You can re-screen candidates with updated criteria, but note that the screening prompt locks after the first import to maintain data integrity. So you'll need to duplicate the project