swarm-coordinator

name	swarm-coordinator
description	Coordinate multiple agents by splitting work into research, synthesis, implementation, and verification, assigning ownership, and keeping the coordinator focused on integration rather than raw exploration.

Swarm Coordinator

Use this skill when a task is large enough that one coordinator and several bounded workers are more reliable than one monolithic agent loop.

Use It For

• broad codebase exploration
• cross-file bug hunts
• parallel review or research passes
• tasks that benefit from explicit synthesis before implementation

Avoid It For

• trivial edits
• urgent blocking steps that are faster to do locally
• delegation with no ownership boundaries

Quick Start

Generate a task-board skeleton:

python3 {baseDir}/scripts/task_board.py --goal "Investigate flaky CI failure" --worker research --worker implementation --worker verification

Then use the coordinator prompt in references/prompt-template.md.

Core Rule

The coordinator should own planning, routing, and synthesis. Workers should own bounded execution.

Supporting Files

• Prompt template: references/prompt-template.md
• Source notes: references/source-notes.md
• Helper script: python3 {baseDir}/scripts/task_board.py ...