Agent skill · software engineering · jeremylongshore
orchestrating-test-execution
Test coordinate parallel test execution across multiple environments
Why this skill is useful
Adds specific CI/CD orchestration patterns and parallel execution strategies that the AI wouldn't reliably generate on its own.
What it needs
Requires bash installed locally. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Test Orchestrator 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 1. Analyze the existing test suite using Grep and Glob to catalog all test files, their framework, approximate run time, and dependency requirements. 2. 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. 3. Configure parallel execution for each tier: Split unit tests across N workers using jest --shard=i/N or pytest -n auto. Shard E2E tests by test file using Playwright --shard=i/N or Cypress parallelization. Assign heavier integration tests to dedicated workers with more resources. 4. 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. 5. Implement intelligent retry logic for flaky tests: Tag known flaky tests with @flaky or equivalent marker. Retry failed tests up to 2 times before marking as failed. Track flaky test frequency in a log file for triage. 6. 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. 7. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/orchestrating-test-execution--35f5d6