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Integrity report

How to read the AI assisted integrity and code quality report, including every signal and score.

Integrity report

After a candidate submits, the platform analyzes their work and produces a report. It appears on the candidate detail page once analysis completes. This page explains what each part means.

Top level scores

Top scoreWhat it measures
CompositeOverall assessment score combining integrity and quality
Integrity aggregateHow trustworthy the submission is
Quality aggregateHow good the code is
ConsistencyHow consistent the work is across problems
RecommendationA hire recommendation bucket

Scores are color coded by threshold, exactly as in the product: above 0.7 is success, above 0.4 is warning, and at or below 0.4 is destructive.

The recommendation uses seven buckets, ordered from strongest to weakest. Each maps to the same color the product uses on candidate rows and the dashboard chart:

Strong Hire Hire Lean Hire Review Lean No Hire No Hire Strong No Hire

If an integrity guard was triggered, a red Integrity Flag is shown alongside the scores.

Integrity signals (anti cheat)

These look for signs a candidate may have had inappropriate help. Each is shown with when it happened, so you can correlate it with the video and code timeline.

SignalMeaning
Natural EvolutionHow much the code developed naturally through normal editing
Bulk Paste SafetyInverse of the probability that large blocks were pasted
Original CodeInverse of the probability that the code was transcribed or copied
Logical CoherenceInverse of the probability of sudden logical leaps inconsistent with the session

A single paste event or a brief tab switch is not proof of cheating. Candidates look things up. Use the video and code replay to judge the context.

Quality signals

Quality is summarized as a radar with eight axes:

  • Code quality
  • Maintainability
  • Readability
  • Efficiency
  • Modularity
  • Code maturity
  • Debugging efficiency
  • Refactor quality

Development metrics

For each problem the report includes behavioral metrics: time to solve, iteration count, judge attempts, lines of code, deletion ratio, and characters per minute. These help distinguish steady work from abrupt insertion.

Per problem and cross problem

The report breaks down each problem individually and also surfaces cross problem patterns: repeated weaknesses, near miss flags, and improvement suggestions. An executive summary ties it together in plain language.

Timeline pins

The report includes timeline pins for each problem. Each pin marks a notable moment (a paste, a struggle, a bug fix, a refactor, a scaffold, an acceptance, or an insight). Clicking a pin seeks the video and loads the code snapshot at that moment.

AI assists, you decide

The report gives scores and a recommendation, but the final hiring decision is yours. Every signal is reviewable alongside the actual video and code, and the screening decision is recorded separately from the model output.

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