> For the complete documentation index, see [llms.txt](https://docs.layerlens.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.layerlens.ai/2.-get-started/first-judge.md).

# Your first judge

Build your first LLM judge in Stratix Premium — define a rubric, test it, optionally GEPA-optimize.

A judge is an LLM that scores subjective dimensions — helpfulness, faithfulness, tone, safety — that a code grader can't grade. Building one takes about 15 minutes.

## Prerequisites

* [ ] A Stratix Premium account ([sign up](/2.-get-started/sign-up.md))
* [ ] A clear definition of what you want to grade (write it in plain English first)
* [ ] At least 10 example outputs labeled "good" or "bad" — more is better

## Steps

### 1. Open Judges

Left rail: **Agent Evaluation → Judges**. Click **New judge**.

### 2. Name and describe

* **Name:** e.g., "helpfulness-customer-support"
* **Description:** what this judge grades, in one sentence
* **Output type:** binary (pass/fail), score (e.g., 1-5), or labeled (e.g., "helpful" / "neutral" / "unhelpful")

### 3. Pick a judging model

The model that runs the rubric. Default is a balanced choice; pick a stronger model for harder rubrics.

### 4. Write the rubric

The rubric is the prompt the judging model uses. Best practices:

* State the dimension you're grading
* Describe what "good" looks like with examples
* Describe what "bad" looks like with examples
* Show the output format you want back

The Premium UI provides a starter template you can adapt.

### 5. Test on a few examples

Paste 3-5 sample outputs and run the judge. Read the verdicts. If they don't match your intuition, iterate the rubric.

### 6. Optional: GEPA-optimize

If you have ≥30 labeled examples, run **GEPA optimization**. Stratix tunes the rubric to better match your labels. Agreement with humans typically rises 10-20 percentage points.

[More about GEPA optimization](/8.-evaluate-score-the-outputs/judges-1.md#judge-optimization-gepa)

### 7. Save

The judge is now reusable in any evaluation, trace evaluation, or agentic evaluation in your org.

## Verify

You should be able to apply your judge to a single sample input/output and get back a verdict.

## What to try next

* **Apply the judge to your first evaluation.** Open the eval, add the judge, rerun.
* **Apply the judge to a trace evaluation.** Real production data, judged.
* **Build a second judge** for a different dimension. Stratix evaluations let you stack many judges.

## Where to next

* [Tutorial: Build your first judge](/8.-evaluate-score-the-outputs/02-first-judge.md)
* [Tutorial: Optimize a judge with GEPA](/9.-improve-tune-the-system/05-gepa-optimize.md)
* [Concept: Judges](/8.-evaluate-score-the-outputs/judges-1.md)
* [Stratix Premium — Judges](/8.-evaluate-score-the-outputs/judges.md)