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    Test Flake Hunter

    by Roy Yuen

    2

    Detect and analyze flaky tests across multiple frameworks with automated repeated execution and severity reporting.

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    See it in action

    You say

    I've noticed some intermittent failures in our authentication tests. Can you run the tests in tests/auth/ 20 times and tell me which ones are flaky?

    Your agent does

    Found 1 flaky test in tests/auth/:

    • test_session_expiry: 14 passes, 6 failures (30% flake ratio). Severity: High. Suggested cause: Race condition in session cleanup timing. Detailed reports saved to flake-report.md and flake-report.json.

    What you get

    Locate intermittent failures that pass on local but fail in CI pipelines.Quantify test reliability using flake ratios and severity classifications.Generate structured JSON reports of test stability for engineering dashboards.Debug race conditions by isolating and repeatedly running specific test files.

    About this skill

    What it does

    Test Flake Hunter is a diagnostic tool designed to identify non-deterministic test failures. It automatically detects your testing framework—supporting pytest, Jest, and Go test—and executes your suite or specific test files multiple times to uncover "flaky" behavior. By comparing pass/fail patterns across runs, it calculates flake ratios and provides structured reports on test reliability.

    Why use this skill

    Manually re-running tests to catch intermittent failures is tedious and prone to human error. This skill automates the repetition, normalizes output from different runners, and applies severity scoring to help you prioritize fixes. It goes beyond simple "pass/fail" by analyzing error messages and execution patterns to suggest likely root causes, such as network timeouts or race conditions.

    Supported Tools

    • Python: pytest, py.test
    • JavaScript/TypeScript: Jest
    • Go: go test
    • Generic: Any runner with standard exit codes via Makefile or custom commands

    Output format

    The skill produces two primary artifacts: a human-readable flake-report.md summary for quick review, and a structured flake-report.json for integration into CI/CD pipelines or further data analysis. Reports include flake ratios, failure message snippets, and suggested remediation steps.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Trust & safety

    Security scanned

    Verified clean 1 month ago

    Listed1 month ago

    Creator

    Roy Yuen
    Roy Yuen

    1075+ total installs · 111 skills on Agensi

    Frequently Asked Questions

    Popular in Testing & QA