A systematic evaluation of each AI response using the classic academic framework: Currency, Relevance, Authority, Accuracy, and Purpose — adapted specifically for AI-generated content.
How it works
CRAAP is an established source-evaluation method originally developed by librarians at California State University, Chico. In SeekBox, the judge (default: Claude) applies the five CRAAP criteria to every engine’s output:
Currency – How up-to-date is the information? Does it reference recent events or data?
Relevance – Does the response directly address your query and your context?
Authority – What credentials or knowledge base does the model draw from? Does it cite verifiable sources?
Accuracy – Are facts verifiable? Are there internal contradictions or known hallucinations?
Purpose – What is the apparent goal of the response? Is bias detectable?
The judge scores each engine on all five criteria and delivers a clear breakdown with an overall “pass/fail” recommendation.
When to use CRAAP Test
Academic research or fact-heavy reports where source quality matters
Medical, legal, or financial queries (always consult professionals, but use CRAAP to triage AI answers)
Evaluating marketing claims or product reviews generated by AI
Teachers assessing student work that used AI assistance
Anyone who wants a standardized, transparent rubric instead of subjective opinion