parallel-dispatch

Execute worker agents in parallel using a Directed Acyclic Graph structure.

Updated Mar 7, 2026

Search Tags:#workflow orchestration #parallel execution #agent dispatch #failure recovery #dag processing #deadlock resolution

Ready to run

npx skills add https://github.com/Geargrindadmin/gg-agentic-harness --skill parallel-dispatch-geargrindadmin

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: parallel-dispatch
Source: https://github.com/Geargrindadmin/gg-agentic-harness/tree/main/.agent/skills/parallel-dispatch
Command: npx skills add https://github.com/Geargrindadmin/gg-agentic-harness --skill parallel-dispatch-geargrindadmin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automates the parallel execution of multiple worker agents, optimizing throughput and managing dependencies within complex workflows.

Core Features & Use Cases

Parallel Group Execution: Dispatches multiple independent tasks simultaneously.
Worker Monitoring & Failure Handling: Tracks worker progress, detects failures, and implements recovery strategies.
Deadlock Detection: Identifies and resolves deadlocks to prevent workflow stalls.
Use Case: In a software build process, compile different modules in parallel to significantly reduce overall build time, while ensuring that dependent modules are built only after their prerequisites are met.

Quick Start

Use the parallel-dispatch skill to execute the tasks defined in the DAG for the current track.

Frequently Asked Questions about parallel-dispatch

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I execute multiple independent tasks in parallel to reduce build times?▼

Parallel execution is managed by dispatching multiple worker agents simultaneously based on a Directed Acyclic Graph. This orchestrates dispatch, monitors progress, and aggregates results to significantly reduce overall processing time for independent operations.

How does DAG processing handle dependencies during workflow orchestration?▼

DAG processing handles dependencies by ensuring dependent tasks execute only after their prerequisites are met. The engine orchestrates dispatch according to the graph structure, tracking worker progress to maintain correct execution order.

What happens if a worker agent fails during concurrent task dispatch?▼

If a worker agent fails during concurrent task dispatch, the system tracks the failure and implements recovery strategies. The engine monitors worker progress continuously to detect failures and prevent workflow stalls.

Can workflow orchestration detect and resolve deadlocks in concurrent agent tasks?▼

Workflow orchestration can detect and resolve deadlocks in concurrent agent tasks. The engine identifies deadlocks specifically to prevent workflow stalls and ensure continuous progress across the worker pool.

Does parallel execution support file lock coordination for shared resources?▼

Parallel execution supports file lock coordination for shared resources. This feature works alongside worker pool management to prevent conflicts when multiple concurrent agents access the same files.