home / skills / proffesor-for-testing / agentic-qe / qe-test-execution
This skill orchestrates parallel QE test execution with smart selection, retry logic, and comprehensive result aggregation to accelerate CI pipelines.
npx playbooks add skill proffesor-for-testing/agentic-qe --skill qe-test-executionReview the files below or copy the command above to add this skill to your agents.
---
name: "QE Test Execution"
description: "Parallel test execution orchestration with intelligent scheduling, retry logic, and comprehensive result aggregation."
---
# QE Test Execution
## Purpose
Guide the use of v3's test execution capabilities including parallel orchestration, smart test selection, flaky test handling, and distributed execution across multiple environments.
## Activation
- When running test suites
- When optimizing test execution time
- When handling flaky tests
- When setting up CI/CD test pipelines
- When executing tests across environments
## Quick Start
```bash
# Run all tests with parallelization
aqe test run --parallel --workers 4
# Run affected tests only
aqe test run --affected --since HEAD~1
# Run with retry for flaky tests
aqe test run --retry 3 --retry-delay 1000
# Run specific test types
aqe test run --type unit,integration --exclude e2e
```
## Agent Workflow
```typescript
// Orchestrate test execution
Task("Execute test suite", `
Run the full test suite with:
- 4 parallel workers
- Retry flaky tests up to 3 times
- Generate JUnit report
- Fail fast on critical tests
Report results and any failures.
`, "qe-test-executor")
// Smart test selection
Task("Run affected tests", `
Analyze changes in PR #123 and:
- Identify affected test files
- Run only relevant tests
- Include integration tests for changed modules
- Report coverage delta
`, "qe-test-selector")
```
## Execution Strategies
### 1. Parallel Execution
```typescript
await testExecutor.runParallel({
suites: ['unit', 'integration'],
workers: 4,
distribution: 'by-file', // or 'by-test', 'by-duration'
isolation: 'process',
sharding: {
enabled: true,
total: 4,
index: process.env.SHARD_INDEX
}
});
```
### 2. Smart Test Selection
```typescript
await testExecutor.runAffected({
changes: gitChanges,
selection: {
direct: true, // Tests for changed files
transitive: true, // Tests for dependents
integration: true // Integration tests touching changed code
},
fallback: 'full-suite' // If analysis fails
});
```
### 3. Flaky Test Handling
```typescript
await testExecutor.handleFlaky({
detection: {
enabled: true,
threshold: 0.1, // 10% flake rate
window: 100 // Last 100 runs
},
strategy: {
retry: 3,
quarantine: true,
notify: ['#flaky-tests']
}
});
```
## Execution Configuration
```yaml
execution:
parallel:
workers: auto # CPU cores - 1
timeout: 30000
bail: false
retry:
count: 2
delay: 1000
only_failed: true
reporting:
formats: [junit, json, html]
include_timing: true
include_logs: true
environments:
- name: node-18
image: node:18-alpine
- name: node-20
image: node:20-alpine
```
## CI/CD Integration
```yaml
# GitHub Actions example
test:
runs-on: ubuntu-latest
strategy:
matrix:
shard: [1, 2, 3, 4]
steps:
- uses: actions/checkout@v4
- name: Run tests
run: |
aqe test run \
--shard ${{ matrix.shard }}/4 \
--parallel \
--report junit
- name: Upload results
uses: actions/upload-artifact@v4
with:
name: test-results-${{ matrix.shard }}
path: reports/
```
## Result Aggregation
```typescript
interface ExecutionResults {
summary: {
total: number;
passed: number;
failed: number;
skipped: number;
flaky: number;
duration: number;
};
shards: ShardResult[];
failures: TestFailure[];
flakyTests: FlakyTest[];
coverage: CoverageReport;
timing: TimingAnalysis;
}
```
## Coordination
**Primary Agents**: qe-test-executor, qe-test-selector, qe-flaky-detector
**Coordinator**: qe-test-execution-coordinator
**Related Skills**: qe-test-generation, qe-coverage-analysis
This skill orchestrates parallel test execution with intelligent scheduling, retry logic for flaky tests, and comprehensive result aggregation. It enables distributed runs across environments, smart test selection, and configurable reporting to speed up feedback loops. Use it to reduce CI time, isolate flaky behavior, and produce unified test metrics for pipelines.
The skill coordinates specialized agents to run tests in parallel, shard workloads, and select only affected tests based on source changes. It applies retry and quarantine strategies for flaky tests, aggregates shard results into a single execution summary, and emits reports in formats like JUnit, JSON, and HTML. Configuration options let you tune workers, sharding, timeouts, and reporting for CI/CD integration.
How are flaky tests detected?
Flaky detection uses a configurable window and threshold based on historical runs; tests exceeding the flake rate are flagged for retry or quarantine.
How do shards get aggregated?
Each shard emits a report and artifact; the coordinator collects shard results to produce a single ExecutionResults summary with failures, flaky tests, coverage, and timing.