Eval Rubric Prompt
Builds a scoring rubric a grader model can apply consistently.
/ quick answer
Use to define model-graded scoring for a subjective AI output. Builds a scoring rubric a grader model can apply consistently.
Create an evaluation rubric for the AI output described below. Return:
1. DIMENSIONS — 3–5 scoring dimensions, each with a one-line definition.
2. SCALE — a 1–5 scale per dimension with concrete descriptions of what each score looks like.
3. AUTOMATIC FAILURES — conditions that force a score of 1 regardless of other qualities.
4. GRADER PROMPT — a ready-to-use prompt that scores one output against this rubric and returns JSON.
5. THRESHOLD — the pass score, with reasoning.
Be concrete enough that two different graders would agree.
Output type: {{OUTPUT_TYPE}}
User goal: {{GOAL}}
Non-negotiables: {{REQUIREMENTS}}1. DIMENSIONS — Accuracy: every claim is supported by the source. Completeness: answers all parts of the question...
/ frequently asked
What does the Eval Rubric Prompt prompt do?
Use to define model-graded scoring for a subjective AI output.
Which AI models work with this prompt?
It is model-agnostic: it works with any capable general model. Replace the bracketed variables with your own context before running it.
How do I use this prompt?
1) Copy the prompt with the copy button. 2) Replace every bracketed variable with your real details. 3) Paste it into your AI assistant. 4) Compare the answer with the example output and ask for changes if needed.
What output should I expect?
1. DIMENSIONS — Accuracy: every claim is supported by the source. Completeness: answers all parts of the question...
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →AI Evaluation
AI evaluation is the measurement layer of an AI system: a fixed set of cases, a scoring method and a tracked pass rate you can regress against.
- →AI Monitoring
AI monitoring is production observability for model-driven systems: traces, cost, latency, tool failures and output-quality drift.
Related workflows
Turn this into a repeatable process.
- →Build an Eval Suite Before Optimising Prompts
Stop guessing whether a change improved anything.
- →Monitor an AI System in Production
See quality, cost and failure drift before your users report it.
Related tool stacks
The tools that run it in production.
- →AI Observability Stack
Traces, cost, evals and quality drift for AI systems in production.
Related prompts
Reusable prompts for this job.
- →AI System Threat Model Prompt
Produces a concrete threat model for an AI system with tool access.
- →AI Code Review Rubric Prompt
A reviewer prompt that finds real defects instead of style opinions.
- →Prompt Improver Prompt
Iterate a weak prompt into a strong one using best practices.
- →Strategic Analyst Prompt
Turn a business situation into a McKinsey-style strategic memo.
Comparisons & alternatives
Pick between the options.
- →Model-Graded Evals vs Assertion Evals
Assertions are cheap, fast and objective; model grading captures quality you cannot express as a rule.