Nova scores each candidate from 1-10 for one role at a time. A high score means the available evidence appears strongly aligned with the criteria for that role. The score is not a percentage, a count of passed criteria, or a hiring decision. It is a screening assessment based on the role, criteria, evidence quality, and remaining uncertainty.Documentation Index
Fetch the complete documentation index at: https://nova.dweet.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
Score Scale
| Score | How to read it |
|---|---|
| 10 | Exceptional evidence alignment. Clear evidence across the role’s core needs, plus unusually strong signals. |
| 9 | Outstanding evidence alignment. Strong evidence for the core requirements and few meaningful concerns. |
| 8 | Strong evidence alignment. Resume-verifiable essentials are supported by evidence. Any remaining gaps are minor or better checked in interview. |
| 7 | Promising evidence alignment. Relevant and useful to review, but there is real uncertainty about at least one important requirement. |
| 6 | Mixed evidence alignment. Some useful evidence, but important gaps or weaker alignment. |
| 5 | Borderline evidence alignment. Possible relevance, but the evidence is thin. |
| 3-4 | Weak evidence alignment. Significant gaps, contradicted requirements, or limited evidence for the role. |
| 1-2 | Very limited evidence alignment. Very little relevant evidence for the role. |
The 7 Vs 8 Line
Most score calibration questions come from the difference between 7 and 8. An 8 means the main resume-verifiable requirements are evidenced. The candidate may still need normal interview checks, but Nova found enough evidence to support the core screening case. A 7 means the candidate is interesting, but something important is still uncertain from the resume or application. That could be a missing skill signal, unclear seniority, thin domain evidence, or an application answer that does not fully resolve a requirement.Evidence Status
When Nova shows criteria analysis, each criterion can be marked:| Status | Meaning |
|---|---|
| Pass | The evidence supports the requirement. Equivalent experience can count when it reasonably satisfies the criterion. |
| Partial | The evidence is related, thin, indirect, or missing enough detail to be confident. |
| Fail | The evidence contradicts the requirement or verifies an exclusion. |
Partial, not Fail. A resume that does not mention a requirement creates uncertainty. A resume that clearly shows the opposite creates a concern.
How Must Have Criteria Work
Must have criteria matter more than Preferred or Nice to have criteria, but they are not automatic score caps. Nova assesses whether the available evidence supports continued review. A candidate with one absent Must have signal may still score around 7 or 8 if the missing detail is plausible to verify. A candidate who clearly contradicts a Must have requirement usually scores much lower. Use Must have only for requirements that are genuinely necessary for the role, such as:- Legal or regulatory eligibility.
- The experience that makes someone viable for the role, such as production backend experience for a backend engineer or current registration for a nurse.
- A practical requirement the job cannot work without.
- A deal-breaker you have explicitly confirmed.
What The Assessment Tells You
- Verdict: The headline screening summary, not a decision.
- Strengths: The strongest evidence Nova found.
- Concerns: Missing, thin, or contradicted evidence.
- Interview Focus: The questions to verify next.
- not evidenced: Nova did not find evidence for the requirement.
- contradicted by: Nova found evidence pointing the other way.
- unverified: The point should be checked with the candidate or hiring team.
When A Score Feels Wrong
| What you see | Likely cause | What to do |
|---|---|---|
| Most candidates score 9-10 | Criteria are too loose or too generic. | Add role-specific requirements and make the key differentiators explicit. |
| Almost no candidates score above 5 | Criteria are too strict or too many items are marked Must have. | Move secondary requirements to Preferred or Nice to have. |
| A candidate you expected to review scored low | Their resume may not show the evidence your criteria ask for. | Check the concerns, then decide whether to edit the criterion or verify the point in interview. |
| Similar candidates score differently | Criteria may be vague or depend on details one resume includes and another omits. | Rewrite the criterion around observable evidence. |
| Everyone clusters around 5-7 | The criteria may describe broad relevance instead of clear differentiators. | Add the requirements that separate acceptable from strong candidates. |
| Tool names drive too much of the score | The criterion may be too vendor-specific. | Reframe around the capability unless that exact tool is required. |
Good Review Workflow
- Read the verdict first.
- Check the strengths and concerns.
- Open criteria analysis when available.
- Decide whether the concern is real, missing from the resume, or better checked in interview.
- Edit criteria only when the pattern repeats across candidates.
Can I weight criteria manually?
Can I weight criteria manually?
There is no separate numeric weighting setup. Use Must have, Preferred, and Nice to have to show importance.
Why did a missing requirement not create a very low score?
Why did a missing requirement not create a very low score?
Absence is uncertainty. Nova treats a missing detail differently from evidence that proves the candidate does not meet the requirement.
Why did a candidate with many passes still get a middling score?
Why did a candidate with many passes still get a middling score?
The passed criteria may be lower importance, generic, or offset by a serious concern. The score reflects overall evidence alignment.
What if a candidate has no resume?
What if a candidate has no resume?
Nova can use a LinkedIn profile URL as a fallback when enabled. If no usable evidence is available, the candidate is skipped and not charged.
Configure Criteria
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AI Candidate Scoring
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