# Flaky Detection

> Detect and analyze flaky tests that fail intermittently. Use this skill when a test fails unexpectedly, the user asks about flaky tests, or test results are inconsistent. Use when this capability is needed.

- Skill: `tomevault-io/flaky-detection` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/flaky-detection`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/flaky-detection/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/flaky-detection

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# Flaky Test Detection

This skill identifies and analyzes flaky tests - tests that pass and fail intermittently without code changes.

## When to Use

- Test fails unexpectedly after passing previously
- User asks "is this test flaky?"
- User asks "why does this test fail sometimes?"
- Test results are inconsistent across runs
- User wants to identify unreliable tests

## How It Works

1. Query test execution history for the failing test
2. Analyze pass/fail patterns over time
3. Identify flakiness indicators:
   - Timing-dependent failures
   - Race conditions
   - External dependencies
   - Resource contention
4. Calculate flakiness score
5. Suggest remediation strategies

## Implementation

Use the following Argus MCP tools:

1. **`argus_quality_stats`** - Get test quality metrics and flakiness scores
   - Input: `{ "project_id": "<project>", "test_id": "<test>" }`
   - Returns: Flakiness score, failure patterns, execution history

2. **`argus_healing_patterns`** - Find common fix patterns for flaky tests
   - Input: `{ "failure_type": "flaky", "test_id": "<test>" }`
   - Returns: Suggested fixes based on similar resolved issues

## Output Format

### Flakiness Analysis

| Test | Flakiness Score | Pattern | Suggested Fix |
|------|-----------------|---------|---------------|
| test_async_upload | 🔴 0.73 | Timing | Add explicit wait for upload completion |
| test_db_connection | 🟡 0.45 | Resource | Use connection pooling |
| test_api_response | 🟢 0.12 | None | Likely not flaky |

### Flakiness Indicators

- **Timing Issues**: Test depends on async operations without proper waits
- **Race Conditions**: Multiple threads/processes competing for resources
- **External Dependencies**: Network, databases, or third-party services
- **State Leakage**: Previous tests affecting current test state

### Remediation Steps

1. Add explicit waits/retries for async operations
2. Isolate test state with fixtures
3. Mock external dependencies
4. Use deterministic test data

---
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