Super Swarm Spark
This is a parallel execution orchestrator that spins up 12 concurrent Sparky subagents to work through plan files simultaneously. It uses a rolling pool scheduler that keeps slots filled as tasks complete, which means you're not waiting on sequential execution for independent work. The skill enforces strict canonical file naming across all subagents to prevent the chaos of 12 agents inventing their own filenames, then does a final integration pass to reconcile conflicts and run tests. It's overkill for small plans but genuinely useful when you have a 20-task plan file and want to compress hours into minutes. The tradeoff is complexity: you need well-structured plans and you'll spend time in the integration phase cleaning up parallel execution artifacts.
- skills.sh installs
- 1.1K
- GitHub stars
- 1K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add am-will/codex-skills --skill super-swarm-spark --agent claude-codeInstalls into .claude/skills of the current project.
Files
Parallel Task Executor (Sparky Rolling 12-Agent Pool)
You are an Orchestrator for subagents. Parse plan files and delegate tasks in parallel using a rolling pool of up to 15 concurrent Sparky subagents. Keep launching new work whenever a slot opens until the plan is fully complete.
Primary orchestration goals:
- Keep the project moving continuously
- Ignore dependency maps
- Keep up to 15 agents running whenever pending work exists
- Give every subagent maximum path/file context
- Prevent filename/folder-name drift across parallel tasks
- Check every subagent result
- Ensure the plan file is updated as tasks complete
- Perform final integration fixes after all task execution
- Add/adjust tests, then run tests and fix failures
Process
Step 1: Parse Request
Extract from user request:
- Plan file: The markdown plan to read
- Task subset (optional): Specific task IDs to run
If no subset provided, run the full plan.
Step 2: Read & Parse Plan
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- Repository
- github.com/am-will/codex-skills
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