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detect-flaky

Detect, diagnose, and fix flaky tests in Python, Go, and JavaScript/TypeScript codebases.

Updated Apr 14, 2026
Search Tags:#flaky tests#test reliability#go testing#javascript testing#ci testing#python testing#test debugging
One-click install
npx skills add https://github.com/kaiohenricunha/dotbabel --skill detect-flaky
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: detect-flaky
Source: https://github.com/kaiohenricunha/dotbabel/tree/main/plugins/dotbabel/templates/claude/skills/detect-flaky
Command: npx skills add https://github.com/kaiohenricunha/dotbabel --skill detect-flaky

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Flaky tests create unreliable CI pipelines, waste developer time on false failure debugging, and erode trust in test suite results. This skill automates the end-to-end process of identifying, diagnosing, and fixing non-deterministic test failures across Python, Go, and JavaScript/TypeScript codebases.

Core Features & Use Cases

  • Multi-language pattern scanning: Detects known flaky test anti-patterns in Python, Go, and JS/TS test files using a curated severity-ranked catalog.
  • Empirical failure detection: Runs test suites repeatedly to catch intermittent failures that static analysis misses.
  • Actionable fix generation: Maps detected issues to concrete before/after code fixes with clear explanations of the flakiness root cause. Use case: A team experiencing random CI test failures can use this skill to automatically identify the root cause (such as unseeded random values or unmocked external dependencies) and receive a ready-to-implement fix.

Quick Start

Use the detect-flaky skill to scan your project's test suite for flaky patterns and get prioritized, actionable fixes for any issues found.

Frequently Asked Questions about detect-flaky

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

FAQPage Schema
How do I find and fix flaky tests in my CI pipeline?▼

To find flaky tests, you can scan test files for known anti-patterns and run suites repeatedly to catch intermittent CI failures. This process diagnoses root causes and generates concrete code fixes to restore test reliability.

What causes non-deterministic test failures in JavaScript and Python testing?▼

Non-deterministic test failures are typically caused by anti-patterns like unseeded random values or unmocked external dependencies. Static pattern scanning detects these specific code issues to pinpoint the exact flakiness root cause.

Does this flaky test detection approach support Go testing codebases?▼

Yes, flaky test detection supports Go testing alongside Python and JavaScript/TypeScript codebases. It applies both static pattern scanning and empirical repeated execution to identify and resolve intermittent failures across these languages.

How do I debug intermittent test failures that only happen sometimes?▼

Debug intermittent failures by running empirical repeated test execution to catch errors that static analysis misses. This detects sporadic issues, performs root cause analysis, and outputs severity-prioritized fixes for the failing tests.

What's the best way to automatically detect test anti-patterns before they break CI?▼

The best way to detect test anti-patterns is using a curated severity-ranked catalog to statically scan test files. This catches known flaky patterns early and provides concrete before and after code fixes to prevent CI breaks.

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