prompt-evaluation（及时评估）

Prompt Evaluation

Evaluate and benchmark AI prompts for quality, consistency, and performance. Score, compare, and optimize your prompts systematically.

Overview

A prompt evaluation framework that helps agents measure prompt quality across multiple dimensions: clarity, specificity, robustness, cost-efficiency, and output consistency. Compare prompt variants and find the optimal version.

Capabilities

1. Quality Scoring

node evaluate.js score --prompt "Summarize the article" --dimensions clarity,specificity,robustness
node evaluate.js score --prompt-file ./prompts/ --output scores.json

Scores prompts on clarity (0-10), specificity (0-10), robustness (0-10), and cost-efficiency (0-10).

2. A/B Comparison

node evaluate.js compare --prompt-a "Summarize" --prompt-b "Write a 3-bullet summary" --trials 50
node evaluate.js compare --config ab-test-config.json

Run statistical A/B tests between prompt variants with significance analysis.

3. Consistency Check

node evaluate.js consistency --prompt "Translate to French" --runs 100 --variance-threshold 0.15
node evaluate.js consistency --temperature 0.7 --top-p 0.9

Measures output consistency across multiple runs to find the most stable prompts.

4. Regression Testing

node evaluate.js regression --baseline v1.0 --current v1.1 --test-suite golden-set.jsonl
node evaluate.js regression --fail-on-degradation 5%

Detects quality regressions between prompt versions using golden test sets.

5. Cost Analysis

node evaluate.js cost --prompt "Long prompt..." --model gpt-4 --estimate-tokens
node evaluate.js cost --compare-prompts --output cost-report.csv

Estimates token usage and costs for different prompt variants and models.

Configuration

{
  "evaluation": {
    "dimensions": ["clarity", "specificity", "robustness", "cost"],
    "scoringModel": "gpt-4",
    "abTest": {
      "trials": 50,
      "significanceLevel": 0.05
    },
    "consistency": {
      "runs": 100,
      "varianceThreshold": 0.15
    },
    "regression": {
      "degradationThreshold": "5%",
      "goldenSet": "./golden-set.jsonl"
    }
  }
}

Use Cases

• Prompt Engineering: Systematically improve prompt quality
• Quality Assurance: Ensure prompts meet quality standards before production
• Cost Optimization: Find prompts that achieve goals with fewer tokens
• Version Control: Track prompt quality across versions
• Agent Tuning: Optimize agent system prompts for consistency