Test Orchestrator
SkillDev tools'Test coordinate parallel test execution across multiple environments
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Details
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What this skill tells your AI
The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/orchestrating-test-execution/SKILL.md and read by Ahel’s review.
Overview
Coordinate parallel test execution across multiple test suites, frameworks, and environments. Manages test splitting, worker allocation, result aggregation, and intelligent retry strategies.
Prerequisites
- Test runner with parallel execution support (Jest, Vitest, pytest-xdist, Playwright, or JUnit 5)
- CI/CD platform configured (GitHub Actions, GitLab CI, CircleCI, or Jenkins)
- Test suite with consistent pass rates (flaky tests identified and tagged)
- Sufficient CI runner resources for parallel worker count
- Test result reporting tool (JUnit XML, Allure, or equivalent)
Instructions
- Analyze the existing test suite using Grep and Glob to catalog all test files, their framework, approximate run time, and dependency requirements.
- Classify tests into execution tiers:
- Tier 1 (Fast): Unit tests with no I/O -- target under 30 seconds total.
- Tier 2 (Medium): Integration tests requiring local services -- target under 3 minutes.
- Tier 3 (Slow): E2E and browser tests -- target under 10 minutes.
- Configure parallel execution for each tier:
- Split unit tests across N workers using
jest --shard=i/Norpytest -n auto. - Shard E2E tests by test file using Playwright
--shard=i/Nor Cypress parallelization. - Assign heavier integration tests to dedicated workers with more resources.
- Split unit tests across N workers using
- Create a CI pipeline configuration that runs tiers in parallel:
- Tier 1 and Tier 2 run concurrently on separate jobs.
- Tier 3 runs after a fast pre-check gate passes.
- Each tier reports results to a unified collection step.
- Implement intelligent retry logic for flaky tests:
- Tag known flaky tests with
@flakyor equivalent marker. - Retry failed tests up to 2 times before marking as failed.
- Track flaky test frequency in a log file for triage.
- Tag known flaky tests with
- Aggregate results from all parallel workers into a single report:
- Merge JUnit XML files from each shard.
- Calculate total pass/fail/skip counts and execution time.
- Identify the slowest tests for optimization targets.
- Write the orchestration configuration to the project's CI config file and validate it with a dry run.
Output
- CI pipeline configuration file (
.github/workflows/test.yml,.gitlab-ci.yml, or equivalent) - Test sharding configuration with worker count and split strategy
- Merged test result report in JUnit XML or JSON format
- Execution timeline showing parallel job durations and bottlenecks
- Flaky test inventory with retry counts and failure patterns
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Shard produces zero tests | Uneven test distribution or incorrect shard index | Verify shard count matches actual test file count; use file-based splitting |
| Worker out of memory | Too many parallel processes on one runner | Reduce --maxWorkers or -n count; increase runner memory; use --workerIdleMemoryLimit |
| Test ordering dependency | Tests pass in isolation but fail in specific shard order | Add --randomize flag; fix shared state leaks; enforce test independence |
| Result aggregation mismatch | Missing shard results due to job timeout | Set job-level timeouts higher than test timeouts; add result upload as a separate step |
| CI cache miss slowing startup | Dependencies not cached between parallel jobs | Configure dependency caching per lockfile hash; use a shared setup job |
Examples
GitHub Actions matrix strategy for Jest sharding:
jobs:
test:
strategy:
matrix:
shard: [1, 2, 3, 4]
steps:
- run: npx jest --shard=${{ matrix.shard }}/4 --ci --reporters=jest-junit
- uses: actions/upload-artifact@v4
with:
name: results-${{ matrix.shard }}
path: junit.xml
merge:
needs: test
steps:
- uses: actions/download-artifact@v4
- run: npx junit-merge -d results-* -o merged-results.xml
pytest-xdist parallel execution:
pytest -n auto --dist worksteal -q --junitxml=results.xml
Playwright sharded execution:
npx playwright test --shard=1/3 --reporter=junit
Resources
- Jest sharding: https://jestjs.io/docs/cli#--shardshardindex-shardcount
- pytest-xdist: https://pytest-xdist.readthedocs.io/
- Playwright test sharding: https://playwright.dev/docs/test-sharding
- GitHub Actions matrix strategy: https://docs.github.com/en/actions/using-jobs/using-a-matrix-for-your-jobs
- JUnit XML merge tools:
Signals
- GitHub stars
- 3k
- Forks
- 415
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
orchestrating-test-execution- Source
- github.com/jeremylongshore/tons-of-skills-marketplace
github.com/jeremylongshore/tons-of-skills-marketplace
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