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Regression Testing

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regression-testing

Strategic regression testing with test selection, impact analysis, and continuous regression management. Use when verifying fixes don't break existing functionality, planning regression suites, or optimizing test execution for faster feedback.

Overview

Publisherproffesor-for-testing
Repositoryagentic-qe
Skill nameregression-testing
Stars
480
Forks
92
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by proffesor-for-testing on GitHub. Read the source before you install it.

Installation

Install the Regression Testing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git /tmp/agentic-qe
mkdir -p .claude/skills
cp -r /tmp/agentic-qe/assets/skills/regression-testing .claude/skills/regression-testing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Regression Testing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Regression Testing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Regression Testing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Regression Testing

<default_to_action> When verifying changes don't break existing functionality:

  1. ANALYZE what changed (git diff, impact analysis)
  2. SELECT tests based on change + risk (not everything)
  3. RUN in priority order (smoke → selective → full)
  4. OPTIMIZE execution (parallel, sharding)
  5. MONITOR suite health (flakiness, execution time)

Quick Regression Strategy:

  • Per-commit: Smoke + changed code tests (5-10 min)
  • Nightly: Extended regression (30-60 min)
  • Pre-release: Full regression (2-4 hours)

Critical Success Factors:

  • Smart selection catches 90% of regressions in 10% of time
  • Flaky tests waste more time than they save
  • Every production bug becomes a regression test </default_to_action>

Quick Reference Card

When to Use

  • After any code change
  • Before release
  • After dependency updates
  • After environment changes

Test Selection Strategies

StrategyHowReduction
Change-basedGit diff analysis70-90%
Risk-basedPriority by impact50-70%
HistoricalFrequently failing40-60%
Time-budgetFixed time windowVariable

Change-Based Test Selection

typescript
// Analyze changed files and select impacted tests
function selectTests(changedFiles: string[]): string[] {
  const testsToRun = new Set<string>();

  for (const file of changedFiles) {
    // Direct tests
    testsToRun.add(`${file.replace('.ts', '.test.ts')}`);

    // Dependent tests (via coverage mapping)
    const dependentTests = testCoverage[file] || [];
    dependentTests.forEach(t => testsToRun.add(t));
  }

  return Array.from(testsToRun);
}

// Example: payment.ts changed
// Runs: payment.test.ts, checkout.integration.test.ts, e2e/purchase.test.ts

CI/CD Integration

yaml
# .github/workflows/regression.yml
jobs:
  quick-regression:
    runs-on: ubuntu-latest
    timeout-minutes: 15
    steps:
      - name: Analyze changes
        id: changes
        uses: dorny/paths-filter@v2
        with:
          filters: |
            payment:
              - 'src/payment/**'
            auth:
              - 'src/auth/**'

      - name: Run affected tests
        run: npm run test:affected

      - name: Smoke tests (always)
        run: npm run test:smoke

  nightly-regression:
    if: github.event_name == 'schedule'
    timeout-minutes: 120
    steps:
      - run: npm test -- --coverage

Agent-Driven Regression

typescript
// Smart test selection
await Task("Regression Analysis", {
  pr: 1234,
  strategy: 'change-based-with-risk',
  timeBudget: '15min'
}, "qe-regression-risk-analyzer");

// Returns:
// {
//   mustRun: ['payment.test.ts', 'checkout.integration.test.ts'],
//   shouldRun: ['order.test.ts'],
//   canSkip: ['profile.test.ts', 'search.test.ts'],
//   estimatedTime: '12 min',
//   riskCoverage: 0.94
// }

// Generate regression test from production bug
await Task("Bug Regression Test", {
  bug: { id: 'BUG-567', description: 'Checkout fails > 100 items' },
  preventRecurrence: true
}, "qe-test-generator");

Agent Coordination Hints

Memory Namespace

aqe/regression-testing/
├── test-selection/*     - Impact analysis results
├── suite-health/*       - Flakiness, timing trends
├── coverage-maps/*      - Test-to-code mapping
└── bug-regressions/*    - Tests from production bugs

Fleet Coordination

typescript
const regressionFleet = await FleetManager.coordinate({
  strategy: 'comprehensive-regression',
  agents: [
    'qe-regression-risk-analyzer',  // Analyze changes, select tests
    'qe-test-executor',             // Execute selected tests
    'qe-coverage-analyzer',         // Analyze coverage gaps
    'qe-quality-gate'               // Go/no-go decision
  ],
  topology: 'sequential'
});

Related Skills


Remember

With Agents: qe-regression-risk-analyzer provides intelligent test selection achieving 90% defect detection in 10% of execution time. Agents generate regression tests from production bugs automatically.

Skill Composition

  • Test failing? → Use /test-failure-investigator to diagnose root cause
  • File a bug → Use /bug-reporting-excellence for proper bug reporting
  • Test selection → Use /risk-based-testing for risk-based prioritization

Gotchas

  • Agent defaults to "run everything" despite being told to select — explicitly constrain with --affected or file list
  • Change-based selection misses transitive dependencies — a model change can break a controller test 3 hops away
  • Flaky tests in regression suites erode trust faster than missing tests — quarantine immediately, don't skip
  • Agent may report "0 regressions" when tests simply weren't run — verify test count in output, not just pass/fail
  • Running full regression in containers often OOMs — use --workers=2 and --shard for CI environments

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Regression Testing AI skill do?

Strategic regression testing with test selection, impact analysis, and continuous regression management. Use when verifying fixes don't break existing functionality, planning regression suites, or optimizing test execution for faster feedback.

Why use Regression Testing on TypingMind?

Because you install it once and use it with any model. Regression Testing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Regression Testing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/proffesor-for-testing/agentic-qe/tree/main/assets/skills/regression-testing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Regression Testing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Regression Testing?

As many as you like. As long as a model supports skills, you can use Regression Testing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Regression Testing AI skill free?

Yes. It is published on GitHub by proffesor-for-testing under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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