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learnprompt / swarm-coordinator

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.

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SKILL.md
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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](./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](./references/prompt-template.md)
  • Source notes: [references/source-notes.md](./references/source-notes.md)
  • Helper script: python3 {baseDir}/scripts/task_board.py ...