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Flaky Test Analyzer

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anhtester
Flaky Test Analyzer

Skill phân tích và khắc phục các automation test không ổn định (flaky tests), xác định root cause và đề xuất fix.

Overview

Publisheranhtester
Repositoryantigravity-testing-kit
Skill nameFlaky Test Analyzer
Stars
149
Forks
57
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by anhtester on GitHub. Read the source before you install it.

Installation

Install the Flaky Test Analyzer 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.
    https://github.com/anhtester/antigravity-testing-kit/tree/main/.agent/skills/flaky_test_analyzer
  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/anhtester/antigravity-testing-kit.git /tmp/antigravity-testing-kit
mkdir -p .claude/skills
cp -r /tmp/antigravity-testing-kit/.agent/skills/flaky_test_analyzer .claude/skills/anhtester-flaky-test-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Flaky Test Analyzer 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 Flaky Test Analyzer 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 Flaky Test Analyzer 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.

Flaky Test Analyzer

Purpose: Identify and resolve unstable automation tests.


When to Use

Use this skill when:

  • A test passes and fails intermittently
  • Test results are inconsistent across runs
  • CI/CD pipeline has unreliable test results

Responsibilities

Detect flaky tests caused by:

  • Unstable locators (dynamic classes, positional xpath)
  • Timing issues (race conditions, slow page loads)
  • Incorrect waits (hard sleep instead of smart waits)
  • Environment dependency (data not cleaned up, external service down)
  • Test data conflicts (shared data between parallel tests)

Analysis Workflow

  1. Detect — Identify the failing test and reproduce the failure
  2. Inspect — Read error logs, stack traces, and screenshots
  3. Classify — Categorize the root cause (locator / timing / data / environment)
  4. Fix — Apply the appropriate fix strategy
  5. Verify — Re-run test multiple times to confirm stability

Common Flaky Causes & Fixes

Unstable Locator

Problem:

//div[3]/button
.css-1n2xyz-btn

Fix: Replace with stable locator following priority in .agent/rules/locator_strategy.md:

  • id, data-testid, name, css selector (stable), xpath (relative)

Timing Issues

Problem:

java
Thread.sleep(3000);       // Hard sleep — BAD
page.waitForTimeout(2000); // Fixed delay — BAD

Fix: Use smart waits as defined in .agent/rules/selenium_rules.md and .agent/rules/playwright_rules.md:

java
// Selenium
WebDriverWait wait = new WebDriverWait(driver, Duration.ofSeconds(10));
wait.until(ExpectedConditions.visibilityOfElementLocated(By.id("result")));

// Playwright
await expect(page.getByRole('button', { name: 'Submit' })).toBeVisible();

Test Data Conflicts

Problem: Tests share mutable data → parallel runs conflict.

Fix: Use unique, traceable random data:

<testName>_<timestamp>@test.com

Stability Checklist

After fixing a flaky test, verify:

  • Locator is unique and stable across reloads
  • No hard sleep or fixed delays
  • Test data is unique and deterministic
  • Test is independent (no dependency on other tests)
  • Test passes 5+ consecutive runs

Rules References

The agent MUST follow these rules when analyzing flaky tests:

  • .agent/rules/locator_strategy.md — Locator stability rules
  • .agent/rules/automation_rules.md — General automation best practices
  • .agent/rules/selenium_rules.md — Selenium wait strategy
  • .agent/rules/playwright_rules.md — Playwright auto-waiting

Frequently asked questions

What does the Flaky Test Analyzer AI skill do?

Skill phân tích và khắc phục các automation test không ổn định (flaky tests), xác định root cause và đề xuất fix.

Why use Flaky Test Analyzer on TypingMind?

Because you install it once and use it with any model. Flaky Test Analyzer 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 Flaky Test Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anhtester/antigravity-testing-kit/tree/main/.agent/skills/flaky_test_analyzer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Flaky Test Analyzer?

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 Flaky Test Analyzer?

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

Is the Flaky Test Analyzer AI skill free?

Yes. It is published on GitHub by anhtester 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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