Evaluating Prompt Quality
How do you know if your prompt is good? You need evaluation metrics. Unlike traditional code, prompts don’t pass/fail – they produce outputs that vary. You need to measure quality along multiple dimensions.
Key Dimensions to Evaluate
- Accuracy: Does the answer correctly answer the question?
- Coherence: Is the response logical and well‑structured?
- Format adherence: Does it follow requested format (JSON, bullet points, etc.)?
- Safety: Does it avoid harmful, biased, or offensive content?
- Conciseness: Does it stay within length limits?
Manual vs. Automated Evaluation
- Manual: Human reads outputs and scores them (accurate but slow).
- Automated: Use another LLM to score outputs (fast, cheaper, but less reliable).
- Hybrid: Auto‑score first, then manually review borderline cases.
Simple Scoring Rubric (1‑5 Scale)
5: Perfect – meets all requirements.
4: Good – minor issues (e.g., extra word).
3: Acceptable – usable but needs editing.
2: Poor – missing key information or wrong format.
1: Unusable – completely wrong or harmful.Using LLM as Judge
Judge prompt: "Rate the following answer on accuracy (1‑5). Only output the number."Two Minute Drill
- Evaluate prompts on accuracy, coherence, format, safety, conciseness.
- Use a 1‑5 rubric for scoring.
- Manual scoring is accurate; automated scoring using an LLM is faster.
- Track scores across prompt versions to measure improvement.
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