dispatch

Coordinate multi-agent task execution through checklist-based plans.

411|19|Updated Feb 17, 2026
One-click install
npx skills add https://github.com/bassimeledath/dispatch --skill dispatch
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dispatch
Source: https://github.com/bassimeledath/dispatch/tree/main/.agents/skills/dispatch
Command: npx skills add https://github.com/bassimeledath/dispatch --skill dispatch

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) and references (resource) components.

What problem does it solve?

Dispatch manages multi-agent task execution by coordinating workers through checklist-based plans.

Core Features & Use Cases

  • Plan-driven orchestration: design tasks as actionable steps and assign to specialized workers.
  • IPC-based questions: workers can ask clarifying questions without losing context.
  • Progress tracking and reporting: monitor task completion and aggregate results.

Quick Start

Provide a clear objective and the skill will generate a plan, spawn workers, and report progress.

Frequently Asked Questions about dispatch

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

FAQPage Schema
How do I orchestrate multi-agent tasks with parallel execution?

Multi-agent orchestration coordinates specialized workers through checklist-based plans to automate task execution. It enforces deterministic steps and progress tracking, enabling parallel execution across software engineering, research, data processing, and operations.

How do AI workers ask clarifying questions without losing context during task planning?

Workers ask clarifying questions without losing context using IPC-based questioning mechanisms. This allows multi-agent execution to pause safely, request necessary information, and resume the planned workflow without dropping intermediate state.

What is the best way to track progress and recover blocked tasks in an AI workflow?

Progress tracking and safe recovery for blocked tasks are handled by monitoring checklist-based plan completion. The system aggregates results and enforces deterministic steps, ensuring blocked operations can resume without losing prior execution context.

Can I use checklist-based task planning for research and data processing operations?

Checklist-based task planning applies to research, data processing, and operations by assigning actionable steps to specialized workers. It accelerates results through parallel execution while maintaining deterministic task tracking and progress reporting.

Do I need dependencies to automate task execution with specialized AI workers?

No external dependencies are required to automate task execution with specialized AI workers. You provide a clear objective, and the system generates a plan, spawns workers, and reports progress autonomously using its internal orchestration logic.