The comparison, side by side
A criteria matrix and weighted scores, with the same standard applied to every candidate.
A fresh perspective for your next decision
A fairer verdict.
A clearer choice.
Your AI knows what you like.
Should that decide what’s best?
FairVerdict is an AI plugin that compares products, frameworks and solutions on their merits. Your criteria. The evidence. A reasoned report — without leaning on your remembered preferences.
Designed for Claude In development
LESS GUT FEELING. MORE GROUNDING.
FairVerdict / Decision reportIllustrative
A decision, explained.
A small team choosing its next framework.
Option AQuick to ship75/100
Option BBuilt to grow80/100
Option CRoom to customize71/100
Option B leads · Balanced
Option B leads on this rubric. Option A can win if shipping sooner becomes the priority.
Inspect the scoring
| Criterion | Weight | A | B | C |
|---|---|---|---|---|
| Speed to delivery | 40% | 9 | 7 | 6 |
| Maintainability | 35% | 6 | 9 | 7 |
| Flexibility | 25% | 7 | 8 | 9 |
Total = sum of (rating × weight) ÷ 10, rounded.
Change the priorities. See the verdict shift.
Fictional options and scores. An interactive explanation of the method, not a live AI evaluation.
A clearer lens forFrameworksDeveloper toolsProducts & servicesCompeting approaches
A clean starting point
Bring your requirements.
Leave the favorites behind.
A useful comparison should understand the decision you’re making, without trying to confirm the answer you already like.
FairVerdict instructs the AI to use your explicit requirements for this comparison and leave past chats, saved memory and unstated preferences out of the assessment.
In the brief
Your actual use case. Budget and constraints. Must-have capabilities. Evidence about each option.
Out of the judgment
Remembered favorites. Previous conversations. Assumptions about your taste. The urge to agree with you.
The method
A fair comparison
starts before the scoring.
A deliberate process gives every candidate the same chance to make its case.
- 01
Set the rules.
Define the decision, candidates, criteria and weights first. Separate must-haves from nice-to-haves before a favorite can emerge.
A shared rubric - 02
Hear every side.
Give each option comparable research effort. Look for strengths and drawbacks, check factual claims and make gaps in evidence visible.
Evidence over reputation - 03
Show the reasoning.
Score against the agreed criteria. Explain the trade-offs. Change the weights to see whether the recommendation still holds up.
A verdict you can question
The report
The answer matters.
The “why” matters more.
Go beyond a ranked list. Understand what drove the result, where the evidence is thin, and what would change the recommendation.
Try the example aboveThe case for each option
Strengths, weaknesses and sources. Clear distinctions between supported facts and uncertain judgments.
The trade-offs behind the verdict
The decisive factors, the compromises and the conditions in which another option makes more sense.
How much the answer depends
Sensitivity to different priorities. If the evidence is weak or the result is too close, the report should say so.
A few good questions
Know what goes
into the verdict.
What can I compare?
Frameworks, libraries, developer tools, products, services and competing approaches. Start with a concrete decision and a shortlist. The more clearly you describe the requirements, the more useful the comparison can be.
Does it ignore all of my context?
No. Requirements you explicitly provide for the current comparison belong in the brief. The skill tells the AI to exclude saved memory, past conversations and unstated personal preferences. This is a procedural safeguard, not a guarantee that a model is technically isolated from context.
Is there always a single winner?
No. Different priorities can favor different options. When scores are close or supporting evidence is weak, a useful report explains the uncertainty rather than forcing a decisive ranking.
How does FairVerdict work with Claude?
The project is being developed as a Claude plugin and custom skill. It supplies the comparison procedure and a scoring helper. Web research, independent verification and score simulations depend on the capabilities available in the host. Visit the GitHub project for publication and setup updates.
Is this page running an AI comparison?
No. The example uses fictional options and fixed ratings to show how criterion weights affect a verdict. Switching priorities recalculates those scores in your browser; it does not call an AI or evaluate real products.
Make room for a different answer
Your next decision
deserves a fair verdict.
Meet FairVerdict. Follow the project as it develops.