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Get Started Free →Skill phân tích và khắc phục các automation test không ổn định (flaky tests), xác định root cause và đề xuất fix.
.claude/skills/bilal140202-flaky-test-analyzer/SKILL.md| Model | Eval pass | Runs |
|---|---|---|
| gemini-3.6-flash | 100% | 10 |
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-10 | ✗→✓ | ▲ Improved | -28% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -25% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -26% | 0% |
| case-02 | ✓→✓ | = Same ✓ | 11% | 0% |
| case-03 | ✓→✓ | = Same ✓ | 0% | 0% |
Purpose: Identify and resolve unstable automation tests.
Use this skill when:
Detect flaky tests caused by:
Problem:
//div[3]/button
.css-1n2xyz-btnFix: Replace with stable locator following priority in .agent/rules/locator_strategy.md:
id, data-testid, name, css selector (stable), xpath (relative)Problem:
javaThread.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();
Problem: Tests share mutable data → parallel runs conflict.
Fix: Use unique, traceable random data:
<testName>_<timestamp>@test.comAfter fixing a flaky test, verify:
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| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 14,847 | 10,386 | -30% | 1 | 1 | 0% | 2,752 | 2,831 | +3% | 0 | 0 | — |
case-02 | pass→pass | 9,097 | 7,281 | -20% | 1 | 1 | 0% | 1,789 | 1,989 | +11% | 0 | 0 | — |
case-03 | pass→pass | 10,545 | 6,407 | -39% | 1 | 1 | 0% | 2,023 | 2,023 | 0% | 0 | 0 | — |
case-04 | pass→pass | 8,412 | 6,770 | -20% | 1 | 1 | 0% | 1,713 | 1,924 | +12% | 0 | 0 | — |
case-05 | fail→fail | 11,422 | 9,195 | -19% | 1 | 1 | 0% | 2,268 | 2,491 | +10% | 0 | 0 | — |
case-19 | pass→pass | 8,597 | 8,870 | +3% | 1 | 1 | 0% | 1,568 | 2,119 | +35% | 0 | 0 | — |
case-06 | pass→pass | 10,985 | 4,648 | -58% | 1 | 1 | 0% | 1,809 | 1,437 | -21% | 0 | 0 | — |
case-07 | pass→pass | 11,833 | 6,732 | -43% | 1 | 1 | 0% | 2,043 | 1,849 | -9% | 0 | 0 | — |
case-08 | pass→pass | 16,692 | 17,015 | +2% | 1 | 1 | 0% | 2,872 | 3,780 | +32% | 0 | 0 | — |
case-09 | pass→pass | 12,234 | 7,865 | -36% | 1 | 1 | 0% | 2,005 | 1,983 | -1% | 0 | 0 | — |
case-10 | fail→pass | 11,081 | 4,243 | -62% | 1 | 1 | 0% | 1,993 | 1,435 | -28% | 0 | 0 | — |
case-11 | pass→pass | 3,977 | 3,602 | -9% | 1 | 1 | 0% | 804 | 1,408 | +75% | 0 | 0 | — |
case-12 | pass→pass | 3,338 | 3,523 | +6% | 1 | 1 | 0% | 658 | 1,336 | +103% | 0 | 0 | — |
case-13 | fail→pass | 7,987 | 1,991 | -75% | 1 | 1 | 0% | 1,388 | 1,036 | -25% | 0 | 0 | — |
case-14 | fail→pass | 7,656 | 1,906 | -75% | 1 | 1 | 0% | 1,407 | 1,035 | -26% | 0 | 0 | — |
case-15 | pass→pass | 10,230 | 8,303 | -19% | 1 | 1 | 0% | 1,762 | 2,125 | +21% | 0 | 0 | — |
case-16 | pass→pass | 14,260 | 5,229 | -63% | 1 | 1 | 0% | 2,134 | 1,577 | -26% | 0 | 0 | — |
case-17 | pass→pass | 6,485 | 1,964 | -70% | 1 | 1 | 0% | 984 | 953 | -3% | 0 | 0 | — |
case-18 | pass→pass | 11,436 | 9,390 | -18% | 1 | 1 | 0% | 1,960 | 2,159 | +10% | 0 | 0 | — |
case-20 | pass→pass | 8,557 | 6,508 | -24% | 1 | 1 | 0% | 1,903 | 2,051 | +8% | 0 | 0 | — |
case-21 | pass→pass | 3,936 | 3,841 | -2% | 1 | 1 | 0% | 824 | 1,503 | +82% | 0 | 0 | — |
case-22 | pass→pass | 6,667 | 8,768 | +32% | 1 | 1 | 0% | 1,434 | 2,389 | +67% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +14 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.