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prompt-regression-tester

Test prompt changes against defined test cases and generate regression reports.

5|Updated Dec 31, 2025
Search Tags:#stability#LLM#regression#quality-assurance#test-cases#prompt-testing
One-click install
npx skills add https://github.com/patricio0312rev/skillset --skill prompt-regression-tester
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-regression-tester
Source: https://github.com/patricio0312rev/skillset/tree/main/templates/ai-engineering/prompt-regression-tester
Command: npx skills add https://github.com/patricio0312rev/skillset --skill prompt-regression-tester

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematically tests prompt changes to prevent regressions in AI-generated outputs across test cases.

Core Features & Use Cases

  • Structured test cases: Define test inputs, contexts, and expected outcomes to validate prompt behavior.
  • Comparison framework: Automatically compare old vs new prompts and compute diffs, with per-test verdicts.
  • Stability metrics: Quantify output consistency and format adherence across versions.
  • Breakage analysis & fixes: Identify root causes and suggest concrete remedies to restore expectations.
  • CI/CD readiness: Produce repeatable reports suitable for automated pipelines.

Quick Start

Create an initial prompt-regression-test suite by defining at least one test case and running the comparison workflow to generate a baseline report.

Frequently Asked Questions about prompt-regression-tester

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I do regression testing on LLM prompts to prevent output regressions?▼

Prompt regression testing systematically validates prompt changes against structured test cases to prevent regressions in AI-generated outputs. It compares old versus new prompts, computes diffs, and provides per-test verdicts to ensure behavior stability.

How do I measure LLM output stability and format adherence across prompt versions?▼

You measure LLM output stability using stability metrics that quantify output consistency and format adherence across prompt versions. The comparison framework automatically calculates diffs to generate per-test verdicts for evaluating changes.

What is the best way to analyze prompt breakage and fix AI output errors?▼

The best way to analyze prompt breakage is using a framework that identifies root causes of output regressions and suggests concrete remedies to restore expectations. This breakage analysis guides safe prompt evolution and fixes.

Can I integrate prompt testing into a CI/CD pipeline for automated quality assurance?▼

Yes, you can integrate prompt testing into a CI/CD pipeline. The framework produces repeatable reports suitable for automated pipelines, enabling end-to-end regression testing and team collaboration for quality assurance.

How do I create a prompt regression test suite and define test cases?▼

To create a prompt regression test suite, define structured test inputs, contexts, and expected outcomes to validate prompt behavior. Run the comparison workflow with at least one test case to generate a baseline report.

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