execute-tasks-parallel

Concurrent execution of multiple code tasks is achieved by spawning dedicated agents for each task, ensuring isolation and reducing overall processing time. The Skill evaluates task dependencies before simultaneous execution.

Parallel task execution handles dependencies through a pre-check analysis phase that evaluates tasks for blockers before execution. This ensures independent tasks run concurrently while maintaining correct execution order for dependent processes.

Parallel processing supports high throughput environments by executing multiple build processes and test suites simultaneously. It manages agents for concurrent execution and runs a full test suite post-execution to verify quality.

The best way to execute independent tasks in parallel without isolation issues is using an agent-based execution model. Each task receives a dedicated agent, ensuring processes remain isolated and efficient throughout concurrent operations.

Error detection and recovery during concurrent task execution work through a robust verification phase. After parallel processing completes, a full test suite runs as a quality gate to identify issues and ensure system stability.

You should not use parallel processing when tasks have strict sequential dependencies that cannot be resolved during pre-check analysis, or when task isolation is not required for your specific workflow.