LLM Response Grader

Grade model responses against custom weighted rubric rules and detect banned-term violations.

Response score

0.0/100 (grade F)

Base 0.0 minus penalties for banned terms.

Rubric checks

Add rubric rules to start grading.

About This Tool

LLM Response Grader applies weighted rubric checks to evaluate response quality consistently. It is useful for prompt iteration, regression checks, and human-in-the-loop QA.

Frequently Asked Questions

Can rules use regex?

Yes. Use syntax like /pattern/i in the third column.

Is score objective?

It is objective relative to your rubric definition, not universal quality truth.

Is response data uploaded?

No. Grading runs locally in your browser.

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LLM Response Grader vs Answer Consistency Checker

Rubric scoring quality vs multi-answer consistency analysis.

AI Reliability Scorecard vs LLM Response Grader

Release-readiness composite score vs rubric-focused response grading.

Prompt Test Case Generator vs LLM Response Grader

Deterministic prompt-eval dataset generation vs weighted response quality scoring.

Workflow Links

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Before This Tool

RAG Context Relevance ScorerRank retrieval chunks for a query with overlap, phrase hits, and redundancy penalties.Output Contract TesterValidate model outputs against contracts: JSON format, required keys, forbidden terms, and length.AI Token CounterEstimate token usage for prompts and texts across AI models. Fast browser-side estimate.

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